Hate crime, cyber security and the experience of crime among children: Findings from the 2010/11 British Crime Survey:

Supplementary Volume 3 to Crime in England and Wales 2010/11

Kevin Smith (Ed.), Deborah Lader, Jacqueline Hoare and Ivy Lau

March 2012 Hate crime, cyber security and the experience of crime among children: Findings from the 2010/11 British Crime Survey

Supplementary Volume 3 to Crime in England and Wales 2010/11

Kevin Smith (Ed.), Deborah Lader, Jacqueline Hoare and Ivy Lau

ISSN 1759-7005

ISBN 978 1 84987 728-2

March 2012 Acknowledgements

This publication and the accompanying web tables have been prepared by staff in the Crime Statistics Programme, which is part of the Home Office Statistics Unit of Home Office Science. The editor and authors are grateful for the support received from: Maya Bhudia, Andrew Britton, Richard Cheeseman, John Flatley, Jennifer Parfremont-Hopkins, Phil Hall, Jenny Innes, Rachel Murphy, Sarah Osborne and Tim Pateman. Special thanks are due to Irene Ogunbor who coordinated the production of the volume.

The editor also thanks David Blunt, the Home Office Chief Statistician and Head of Profession for Statistics for his support and guidance during the preparation of this report. Thanks also to colleagues who commented on a draft report during quality assurance of this bulletin and to colleagues in the Communications Development Section who assisted in preparing the report.

We would also like to thank staff involved in the work on the British Crime Survey (BCS) at TNS-BMRB, the interviewers working on the BCS and members of the public who kindly agreed to take part in the survey.

Further information

This publication should be read in conjunction with the User Guide to Home Office Crime Statistics, a useful reference guide with explanatory notes regarding the issues and classifications which are key to the production and presentation of the crime statistics: http://www.homeoffice.gov.uk/publications/science-research-statistics/research-statistics/crime-research/user-guide-crime-statistics/

Copies of other Home Office publications are available from the Home Office Science Internet pages: http://www.homeoffice.gov.uk/science-research/research-statistics/ The dates of forthcoming publications are pre-announced and can be found via the UK National Statistics Publication Hub: http://www.statistics.gov.uk/hub/index.html

For further information about the British Crime Survey and police recorded crime statistics, please email crimestats@homeoffice.gsi.gov.uk or write to: Home Office Statistics, 5th Floor, Peel Building, 2 Marsham Street, London, SW1P 4DF

Home Office Responsible Statistician David Blunt, Chief Statistician and Head of Profession for Statistics Contact via crimestats@homeoffice.gsi.gov.uk

The United Kingdom Statistics Authority has designated these statistics as National Statistics, in accordance with the Statistics and Registration Service Act 2007 and signifying compliance with the Code of Practice for Official Statistics. Designation can be broadly interpreted to mean that the statistics: meet identified user needs; are well explained and readily accessible; are produced according to sound methods; and are managed impartially and objectively in the public interest. Once statistics have been designated as National Statistics it is a statutory requirement that the Code of Practice shall continue to be observed.

This statistical bulletin is produced to the highest professional standards and is free from political interference. It has been produced by statisticians working in the Home Office Statistics Unit in accordance with the Home Office’s Statement of Compliance with the Code of Practice for Official Statistics, which covers our policy on revisions and other matters. The Home Office Statistics Unit works under the direct line management of the Home Office Chief Statistician, who reports to the National Statistician with respect to all professional statistical matters. From April 2012 publication of Crime Statistics bulletins will transfer to the Office for National Statistics.

# Contents

| Section | Page | |------------------------------------------------------------------------|------| | Introduction | 7 | | Conventions used in figures and tables | 8 | | List of figures | 9 | | List of tables | 10 | | Chapter 1 The extent of and perceptions towards hate crime | 13 | | *Deborah Lader* | | | 1.1 Summary | 13 | | 1.2 Introduction | 14 | | 1.3 Extent of hate crime | 17 | | 1.4 Repeat victimisation | 19 | | 1.5 Reporting hate crime | 20 | | 1.6 Victim satisfaction with the police | 20 | | 1.7 Effects of hate crime | 22 | | 1.8 Worry about hate crime and perceptions of the likelihood of victimisation | 23 | | 1.9 Age and gender-motivated hate crime | 25 | | 1.10 Other sources of hate crime data | 25 | | Chapter 2 Use of the internet and cyber security | 41 | | *Jacqueline Hoare* | | | 2.1 Summary | 41 | | 2.2 Introduction | 42 | | 2.3 Levels of internet use | 42 | | 2.4 What the internet is used for | 43 | | 2.5 Worry about security of personal details | 45 | 2.6 Protecting personal details ................................................................. 46 2.7 Perceived barriers to internet use ...................................................... 48 2.8 Negative experiences while using the internet ................................. 50

Chapter 3 Experimental statistics on the experience of crime among children aged 10 to 15 ................................................................. 65

Ivy Lau and Jacqueline Hoare

3.1 Summary ......................................................................................... 65 3.2 Introduction ..................................................................................... 66 3.3 The nature of violence ..................................................................... 67 3.4 The nature of theft .......................................................................... 70 3.5 Variation in victimisation rates among children .............................. 72

Bibliography .......................................................................................... 83 Introduction

This bulletin is the third and final in a series of supplementary volumes that accompany the main annual Home Office Statistical Bulletin, ‘Crime in England and Wales 2010/11’ (Chaplin et al., 2011). These supplementary volumes report on additional analysis not included in the main annual publication.

This bulletin covers three topic areas. These are:

The extent of and perceptions towards hate crime

This chapter contains analysis of figures from the 2009/10 and 2010/11 British Crime Surveys, including extent and reporting of hate crime, its effects on victims and victim satisfaction with the police. It also looks at a range of public perception measures relating to hate crime. Questions were asked of adults aged 16 or over in England and Wales.

Use of the internet and cyber security

This chapter contains information from the 2010/11 British Crime Survey on levels of internet use, concerns people may have about using the internet, and any measures taken to protect personal details when using the internet. Variations by age and sex are highlighted throughout the chapter. Questions were asked of adults aged 16 or over in England and Wales.

Experimental statistics on the experience of crime among children aged 10 to 15

This chapter is based on data collected from 10 to 15 year olds who took part in the 2010/11 British Crime Survey. Questions were asked of children in England and Wales who had experienced a crime about the circumstances of the incident, any details on the offender(s) and their views of the incident. Experimental statistics is a designation for statistics still in a development phase. Conventions used in figures and tables

Table abbreviations

‘0’ indicates no response in that particular category or less than 0.5% (this does not apply when percentages are presented to one decimal point).

‘n/a’ indicates that the BCS question was not applicable or not asked in that particular year.

‘-’ indicates that the BCS data are not reported because the unweighted base is less than 50.

‘\*\*\*’ indicates for BCS that the change is statistically significant at the five per cent level. Where an apparent change over time is not statistically significant this is noted in the text.

Unweighted base

All BCS percentages and rates presented in the tables are based on data weighted to compensate for differential non response. Tables show the unweighted base which represents the number of people/households interviewed in the specified group.

Percentages

Row or column percentages may not add to 100% due to rounding. Most BCS tables present cell percentages where the figures refer to the percentage of people/households who have the attribute being discussed and the complementary percentage, to add to 100%, is not shown. A percentage may be quoted in the text for a single category that is identifiable in the tables only by summing two or more component percentages. In order to avoid rounding errors, the percentage has been recalculated for the single category and therefore may differ by one percentage point from the sum of the percentages derived from the tables.

Year-labels on BCS figures and tables

Year-labels on BCS figures and tables identify the BCS year of interview. Respondents’ experience of crime relates to the 12 full months prior to interview (i.e. a moving reference period).

‘No answers’ (missing values)

All BCS analysis excludes don’t know/refusals unless otherwise specified.

Numbers of BCS incidents

Estimates are rounded to the nearest 10,000.

# List of figures

| Chapter 1 | The extent of and perceptions towards hate crime | 13 | |-----------|-----------------------------------------------|----| | Figure 1.1 | Victim satisfaction with the police, 2009/10 and 2010/11 BCS | 21 | | Figure 1.2 | Emotional impact of hate crime incident, 2009/10 and 2010/11 BCS | 22 | | Figure 1.3 | Perceptions of crime by ethnic group, 2009/10 and 2010/11 BCS | 24 |

| Chapter 2 | Use of the internet and cyber security | 41 | |-----------|--------------------------------------|----| | Figure 2.1 | Types of activities that the internet is used for among internet users aged 16 and over, 2010/11 BCS | 44 | | Figure 2.2 | Variation by age in use of activities among internet users aged 16 and over, 2010/11 BCS | 44 | | Figure 2.3 | Proportion of internet users aged 16 and over taking measures to protect personal details online, 2010/11 BCS | 47 | | Figure 2.4 | Proportion of internet users aged 16 and over who experienced a computer virus in the last 12 months by age, sex and internet usage, 2010/11 BCS | 51 |

| Chapter 3 | Experimental statistics on the experience of crime among children aged 10 to 15 | 65 | |-----------|-----------------------------------------------|----| | Figure 3.1 | Proportion of violent incidents experienced by children and adults by timing of incident, 2010/11 BCS | 68 | | Figure 3.2 | Proportion of violent incidents experienced by children and adults by relationship to the offender, 2010/11 BCS | 69 | | Figure 3.3 | Variation in violence victimisation rate among children aged 10 to 15 by household income, 2010/11 BCS | 74 | List of tables

Chapter 1 The extent of and perceptions towards hate crime ............................................... 13

Table 1a Percentage of incidents that were identified as hate crime by type of incident .......... 18 Table 1.01 Number of incidents of hate crime and all BCS crime, by monitored strand .......... 27 Table 1.02 Incidence rate of hate crime and all BCS crime, by monitored strand ................. 27 Table 1.03 Proportion of adults and households who were victims of hate crime and all BCS crime, by monitored strand ................................................................. 28 Table 1.04 Proportion of adults who were victims of hate crime and all BCS crime, by personal characteristics .......................................................................................... 29 Table 1.05 Proportion of adults and households who were victims of hate crime and all BCS crime, by household and area characteristics .................................................. 30 Table 1.06 Proportion of adults who were victims of racially-motivated hate crime, by ethnic group .................................................................................................................. 31 Table 1.07 Proportion of adults who were victims of religion-motivated hate crime, by ethnic group and religion .............................................................................................. 32 Table 1.08 Proportion of adults who were victims of sexual-orientation-motivated hate crime, by age and sex ........................................................................................................ 32 Table 1.09 Proportion of adults who were victims of disability-motivated hate crime, by employment status and presence of long-standing illness or disability .................. 33 Table 1.10 Number of times victims were victimised in previous year .................................. 33 Table 1.11 Proportion of BCS crime incidents reported to the police ...................................... 34 Table 1.12 Reasons for not reporting crime incident to the police ........................................ 34 Table 1.13 Satisfaction with police handling of crime incidents ............................................ 35 Table 1.14 Emotional impact of crime incident ...................................................................... 35 Table 1.15 Perceptions of racially-motivated hate crime, by ethnic group .............................. 36 Table 1.16 Age- and gender-motivated hate crime ................................................................. 37 Table 1.17 Proportion of adults who were victims of age-motivated hate crime, by age and sex .......................................................................................................................... 38 Table 1.18 Proportion of adults who were victims of gender-motivated hate crime, by age and sex ...................................................................................................................... 39 Chapter 2 Use of the internet and cyber security ................................................................. 41 Table 2a Negative experiences in the last year among internet users aged 16 and over ....... 51 Table 2.01 Proportion of adults using the internet in the last year, by age and sex .............. 54 Table 2.02 Frequency of internet use among adults who used the internet in the last year, by age and sex ........................................................................................................ 55 Table 2.03 Internet activities among adults who used the internet in the last year, by age, sex and internet usage ......................................................................................... 56 Table 2.04 Proportion of adults who had used the internet in the last year for each activity who were worried about the security of personal details entered online for that activity ... 57 Table 2.05 Proportion of adults who had used the internet in the last year for each activity who were worried about the security of personal details entered online for that activity, by age, sex and internet usage ....................................................................................... 58 Table 2.06 Measures taken by adults who used the internet in the last year to protect personal details online, by age, sex and internet usage .................................................. 59 Table 2.07a Reasons for not using the internet for buying goods or services among adults who used the internet in the last year, by age, sex and internet usage ......................... 60 Table 2.07b Reasons for not using the internet for online banking or managing finances among adults who used the internet in the last year, by age, sex and internet usage .......... 61 Table 2.07c Reasons for not using the internet for online government services among adults who used the internet in the last year, by age, sex and internet usage ....................... 62 Table 2.08 Negative experiences in the last year among internet users, by age, sex and internet usage .................................................................................................................. 63

Chapter 3 Experimental statistics on the experience of crime among children aged 10 to 15 ....................................................................................................................... 65 Table 3.01 Experimental statistics: Where incidents experienced by children aged 10 to 15 took place .............................................................................................................. 76 Table 3.02 Experimental statistics: Timing of when incidents experienced by children aged 10 to 15 took place .................................................................................................. 76 Table 3.03 Experimental statistics: Offender characteristics in incidents experienced by children aged 10 to 15 .............................................................................................. 77 Table 3.04 Experimental statistics: What injuries were sustained in violent incidents experienced by children aged 10 to 15 .............................................................................. 78 Table 3.05 Experimental statistics: What weapons were used in violent incidents experienced by children aged 10 to 15 .................................................................................. 78 | Table 3.06 | Experimental statistics: Perceptions of incidents experienced by children aged 10 to 15 | 79 | | Table 3.07 | Experimental statistics: Who incidents experienced by children aged 10 to 15 were reported to | 79 | | Table 3.08 | Experimental statistics: What items were stolen in thefts experienced by children aged 10 to 15 | 80 | | Table 3.09 | Experimental statistics: Proportion of children aged 10 to 15 who experienced victimisation in the last year, by personal characteristics | 81 | | Table 3.10 | Experimental statistics: Proportion of children aged 10 to 15 who experienced victimisation in the last year, by household and area characteristics | 82 | 1 The extent of and perceptions towards hate crime

Deborah Lader

1.1 SUMMARY

This chapter presents findings from the 2009/10 and 2010/11 British Crime Survey (BCS). Data from the two survey years have been combined to provide more robust estimates of hate crime. Hate crime is any crime which is perceived as having been motivated (entirely or partially) by a hostility or prejudice to a personal characteristic or perceived personal characteristic, such as ethnicity or religion.

- The 2009/10 and 2010/11 BCS showed that 0.5 per cent of adults were victims of hate crime in the 12 months prior to interview. A similar percentage were victims of personal hate crime and household hate crime (0.2%). In comparison, 22 per cent of adults were victims of at least one BCS crime overall.

- The monitored strand most commonly perceived by the victim as an offender’s motivation for committing a crime was the victim’s race (accounting for an estimated 136,000 incidents on average per year).

- Hate crime was more likely to be repeatedly experienced for household crime offences than for personal crime offences; 37 per cent of victims of household hate crime had been victimised more than once, compared with 19 per cent of victims of personal hate crime. This difference is larger than that found in the BCS overall (29% of victims of BCS household crime were repeat victims, compared with 21% of victims of BCS personal crime).

- The police were more likely to come to know about hate crime than BCS crime overall; 49 per cent of incidents of hate crime came to the attention of the police compared with 39 per cent of incidents of BCS crime overall.

- Fifty-three per cent of hate crime victims were satisfied with the police handling of the hate crime incident (33% were very satisfied and 21% were fairly satisfied) and 45 per cent were not satisfied. Victims of hate crime were less satisfied with this police contact than victims of BCS crime overall: 53 per cent and 69 per cent respectively were satisfied (very or fairly).

- In only 45 per cent of incidents of hate crime, victims thought the police took the matter as seriously as they should, compared with 65 per cent of incidents of BCS crime overall.

- Victims of hate crime were less likely to think the police had treated them fairly or with respect, compared with victims of BCS crime overall. For example, in 63 per cent of hate crime incidents victims thought the police treated them fairly, compared with 79 per cent of incidents of BCS crime overall. Similarly, in 76 per cent of incidents of hate crime, victims thought the police treated them with respect, compared with 89 per cent of incidents of BCS crime overall.

- Victims of hate crime were more likely than victims of BCS crime overall to say they were emotionally affected by the incident (92% and 86% respectively).

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1 Monitored hate crime covers five ‘strands’: disability; race; religion/faith; sexual orientation; and gender-identity. The BCS asks about the first 4 of these. Questions on gender identity were added to the BCS in 2011/12. See Section 1.2 for further discussion of hate strands. 1.2 INTRODUCTION

This is the first Home Office Statistics publication to produce information on hate crime, although breakdowns of overall crime and individual crime types have been shown by different characteristics (age, sex, ethnicity, etc.) in previous publications (Chaplin et al., 2011, Botherby et al., 2011).

Challenge it, Report it, Stop it: The Government’s Plan to Tackle Hate Crime sets out the challenges faced in tackling hate crime. It brings together activity by a wide range of Government Departments – working with local agencies and voluntary sector organisations, as well as with its Independent Advisory Group on Hate Crime – to meet three key objectives to: prevent hate crime happening in the first place; increase reporting and victims’ access to support; and improve the operational response to hate crimes.

In 2007, the police, Crown Prosecution Service (CPS), Prison Service (now the National Offender Management Service) and other agencies that make up the criminal justice system agreed a common definition of ‘hate crime’ and five ‘strands’ that would be monitored centrally:

‘Hate crime is defined as any criminal offence which is perceived, by the victim or any other person, to be motivated by a hostility or prejudice towards someone based on a personal characteristic.’

The five monitored strands are:

- disability;
- gender-identity;
- race;
- religion/faith; and
- sexual orientation.

These characteristics are referred to as equality strands. Primarily, this was to ensure a consistent working definition to allow accurate recording and monitoring. Crimes based on hostility to age, gender, or appearance, for example, can also be hate crimes, although they are not centrally monitored.

Hate crime can take many forms including:

- physical attacks such as assault, grievous bodily harm and murder, damage to property, offensive graffiti and arson;
- threat of attack including offensive letters, abusive or obscene telephone calls, groups hanging around to intimidate, and unfounded, malicious complaints; and
- verbal abuse, insults or harassment – taunting, offensive leaflets and posters, abusive gestures, dumping of rubbish outside homes or through letterboxes, and bullying at school or in the workplace.

2 Botcherby, et al. (2011) conducted an analysis of a combined 2007/08, 2008/09 and 2009/10 BCS dataset to look at hate crime incidents in England and Wales for the Equality and Human Rights Commission. The research paper looked at different equality groups’ expectations about being insulted and their experience of intimidation, threats, violence and crime. It also analysed the experience and reporting of hate crime.

3 http://www.homeoffice.gov.uk/publications/crime/hate-crime-action-plan/

4 http://cps.gov.uk/news/fact_sheets/hate_crime/index.html The extent of and perceptions towards hate crime

Whether a crime or incident is hate-related has a subjective element as it relies on an individual’s perceptions and reporting of the incident and so what is included or excluded may vary between individuals.

The police have been recording reported hate crimes since 1 April 2008 for the five monitored strands listed above. Figures (covering England, Wales and Northern Ireland for 2009) were first published by The Association of Chief Police Officers (ACPO) in 2010, and figures for 2010 were published in September 2011. Further details can be found in Section 1.10.

Measuring hate crime on the British Crime Survey

The British Crime Survey (BCS) is a face-to-face victimisation survey in which people resident in households in England and Wales are asked about their experiences of crime in the 12 months prior to interview. Due to the low volume of hate crime offences the figures are too unreliable to report for a single year of the BCS. Data from two survey years (2009/10 and 2010/11) have therefore been combined to give more robust estimates by increasing the number of incidents available for analysis. Hence for the combined 2009/10 and 2010/11 BCS, the analysis includes incidents experienced by respondents between April 2008 and February 2011. It should be noted that figures reported in this chapter are 12-month averages of the estimates from the two survey years and so are comparable with 12-month BCS estimates presented elsewhere in this and other Home Office Statistics bulletins. Given this longer reference period, there are limitations to how findings can be generalised to the population as a whole, so the findings should be used as a guide to the level of hate crime.

The BCS question on whether an incident was motivated by race was first introduced in 1988, and has been kept as a separate question since then. BCS information on racially-motivated hate crime has been previously published in the Ministry of Justice’s publication on Race and the Criminal Justice System.

Religiously-motivated hate crime used to be asked about as a separate question (in the 2005/06 and 2006/07 BCS) but was merged into the main BCS question when further hate crime questions referring to sexual orientation, age and disability were introduced in 2007/08. In 2009/10, gender was added as a motivation, and transgender or gender identity was added as a motivation to the 2011/12 survey; hence results are not yet available. Details of the questions are in Box 1.1 overleaf.

Police recorded crime provides good coverage of well-reported crimes committed against the public and enable police force level analysis of hate crime. The BCS crime estimates are higher than the number of crimes recorded by the police as the survey captures offences that are not reported to or recorded by the police. Together the BCS and police recorded crime provide a more comprehensive picture than could be obtained from either series alone.

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5 http://www.acpo.presscentre.com/Press-Releases/ACPO-publishes-hate-crime-data-for-2010-111.aspx 6 See Section 2.4 of the User Guide for details of reference periods. 7 Statistics on Race and the Criminal Justice System available at: http://www.justice.gov.uk/downloads/publications/statistics-and-data/mojstats/stats-race-cjs-2010.pdf. Box 1.1 2009/10 and 2010/11 BCS questions (Victimisation module)

The following question was asked of all respondents who mentioned an incident in the screening module:

Do you think the incident was RACIALLY motivated?

- Yes
- No
- Don’t Know

Asked of all respondents who responded ‘Don’t know’ above:

Was there anything about the incident that made you think it might have been RACIALLY motivated?

- Yes
- No

The following question was asked of all respondents who mentioned an incident in the screening module:

Looking at the things on this card do you think the incident was motivated by the offender’s attitude towards any of these factors? (Respondents were asked to choose all options from a card they were shown):

- Your religion or religious beliefs
- Your sexuality or sexual orientation
- Your age
- Your gender
- Any disability you have
- Don’t Know
- None of these

Asked of all respondents who responded ‘Don’t know’ above:

Was there anything about the incident that made you think it MIGHT have been motivated by any of these factors? (Respondents were asked to choose all options from a card they were shown):

- Your religion or religious beliefs
- Your sexuality or sexual orientation
- Your age
- Your gender
- Any disability you have
- None of these

Limitations of the BCS questions

The BCS does not ask about hate crime directly as the concept is not well understood by the public and is likely to lead to under-reporting. Instead, victims are asked about their perception of the offender’s motivation for the incident which is an indirect measure as it represents the victim’s perceptions of the offender’s motivation for the crime. This may result in some over-reporting since it is possible that some crimes considered here as hate crimes may actually be more a result of the victim’s vulnerability to crime, for example, distraction burglary, or an assumption on the victim’s behalf that the crime was motivated by the offender’s attitude. Conversely, a victim might be unaware that they were targeted due to a personal characteristic covered by the hate crime strands.

The BCS may over- or under-represent people who are more susceptible to hate crime. For example, people with a disability might find it more difficult to take part in the survey if their disability impacts on their ability to communicate in particular. Conversely, response rates to the survey might be higher among victims than non-victims as the topic seems more relevant to them.

Moreover, there may also be other characteristics underlying those covered by the equality strands which mean that the victim is more at risk of particular crime types. For example, findings from the BCS have consistently shown that young people aged 16 to 24 are more likely to be victims of crime and it is known that particular Black and Minority Ethnic groups have a lower age profile than that for the general population in England and Wales.

It should also be noted that although the BCS asks whether or not the victim perceived the incident to be motivated by an equality strand (for example, his or her disability status), it is possible in the cases of household crimes that it was someone else in the household that has the characteristic.

1.3 EXTENT OF HATE CRIME

According to the 2009/10 and 2010/11 BCS, there were around 260,000 incidents of hate crime a year, compared with around 9,561,000 incidents of crime overall in the BCS (Table 1.01).

Of the monitored strands asked about in the 2009/10 and 2010/11 BCS (race, religion, sexual orientation and disability), the strand most commonly perceived as an offender’s motivation for committing a crime was the offender’s attitude to the victim’s race (around 136,000 incidents on average a year). The equality strand least commonly perceived as an offender’s motivation for committing a crime was the victim’s religion (Table 1.01).

Incidents relating to the offender’s attitude towards the victim’s age and gender, which are not monitored strands, are shown in Section 1.9.

The BCS provides estimates of the levels of personal and household crimes experienced by adults in England and Wales. Personal crimes relate to all crimes against the individual and only relate to the respondent’s own personal experience (not that of other people in the household). Household crimes are considered to be all property-related crimes and respondents are asked whether anyone currently residing in the household has experienced any incidents within the reference period.

The 2009/10 and 2010/11 combined BCS shows there were around 151,000 incidents of personal hate crime and 109,000 incidents of household hate crime a year, compared with around 3,700,000 incidents of personal crime and 5,861,000 incidents of household crime a year overall in the BCS (Table 1.01).

Three per cent of crime incidents overall in the BCS (4% of BCS incidents of personal crime and 2% of BCS incidents of household crime) were perceived to be hate crime incidents. The proportion of incidents that were perceived to be hate crime varied by crime type from one per cent or fewer of household theft incidents to ten per cent of robbery incidents (Table 1a).

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8 The 9,561,000 incidents of crime overall in the BCS is the average of the 9,503,000 and 9,618,000 incidents reported in the 2009/10 and 2010/11 BCS. 9 See Section 2.5 of the User Guide for a discussion of measures of BCS crime. Table 1a Percentage of incidents that were identified as hate crime, by type of incident

| Type of incident | Unweighted base | % of incidents that were perceived as hate crime | |----------------------------------------|-----------------|-------------------------------------------------| | PERSONAL CRIME | | | | Assault with minor injury or no injury | 6 | 1,603 | | Wounding | 6 | 608 | | Robbery | 10 | 350 | | Theft from person | 1 | 876 | | Other theft of personal property | 1 | 1,579 | | ALL PERSONAL CRIME | 4 | 5,016 | | HOUSEHOLD CRIME | | | | Vandalism | 3 | 6,145 | | Burglary | 3 | 2,002 | | Vehicle-related theft | 0 | 3,651 | | Bicycle theft | 1 | 1,538 | | Other household theft | 1 | 1,538 | | ALL HOUSEHOLD CRIME | 2 | 17,058 | | ALL BCS CRIME | 3 | 22,074 |

1. Base is all BCS crime incidents.

According to the 2009/10 and 2010/11 BCS there were an estimated:

- thirty-four incidents per 10,000 adults of personal hate crime (compared with 827 incidents per 10,000 adults of BCS personal crime overall); and

- forty-seven household hate crime incidents per 10,000 households (compared with 2,510 incidents per 10,000 households of BCS household crime overall; Table 1.02).

The combined 2009/10 and 2010/11 BCS estimates that 0.5 per cent of adults were victims of hate crime in the 12 months prior to interview. A similar percentage were victims of personal hate crime (0.2%) and household hate crime (0.2%). Overall, 21.5 per cent of adults were victims of BCS crime (Table 1.03).

Analysis of victimisation by personal and household characteristics showed that for personal hate crime (as with BCS crime overall, Chaplin et al., 2011), the risk of being a victim varied by socio-demographic characteristics. The risk of being a victim of personal hate crime was highest, for example, among (Table 1.04):

- people aged 16 to 24 (0.6% experienced personal hate crime compared with, for example, fewer than 0.05% of those aged 75 and over);

- people in ethnic groups other than White (0.8% compared with 0.2% of White adults);

- those whose marital status was single (0.6% compared with 0.1% of married adults); The extent of and perceptions towards hate crime

- the unemployed (0.8% compared with 0.2% of adults in employment);

- those with a long-standing illness or disability that limits their daily activities (0.4% compared with 0.2% of those with no long-standing illness or disability); or

- those who visit night clubs at least once a week (1.0% compared with 0.2% of those who did not visit nightclubs at all in the last month).

It should be noted that differences in victimisation rates between ethnic groups may be at least partly attributable to factors other than ethnicity. Previous research (Jansson, 2006; Salisbury and Upson, 2004) has shown that people with a Mixed ethnic background are most at risk of crime. However, multivariate analyses identified that, for the key crime types, ethnicity was not independently associated with the risk of victimisation (Jansson et al., 2007). The proportion of young people in the Mixed ethnic group was, for example, found to be large in comparison to other ethnic groups; and young people are at a higher risk of victimisation (Flatley et al., 2010). There are also inter-relationships between other personal characteristics.

The risk of being a victim of household hate crime was highest among, for example, people who (Table 1.05):

- lived in flats or maisonettes (0.4% experienced household hate crime compared with, for example, 0.1% of those living in a detached house);
- lived in a household with a total income of less than £10,000 (0.5% compared with 0.1% among those who lived in households with a total income of £50,000 or more);
- lived in a ‘multicultural’ area (0.6% compared with 0.1% of those who lived in a ‘countryside’ area); or
- lived in an ‘urban’ area (0.3% compared with 0.1% of those who lived in ‘rural’ areas).

Tables 1.06 to 1.09 show the prevalence of hate crime for the separate equality strands by key personal characteristics. For example, the prevalence of racially-motivated crime is shown by ethnic group and the prevalence of disability-motivated hate crime is shown by long-term illness or disability. It can be seen that respondents with the personal characteristic they report as being a factor that they perceived motivated the incident were more likely to be at risk of being a victim of hate crime. For example, 0.2 per cent of adults who said they had a long-standing illness or disability that limited their daily activities said they were victims of disability motivated hate crime, compared with fewer than 0.05 per cent of respondents who had no long-standing illness or disability.

1.4 REPEAT VICTIMISATION

Repeat victimisation is defined here as being a victim of the same type of crime more than once in the last year. Levels of repeat victimisation account for differences between BCS estimates of incidence rates (see Table 1.02) and victimisation rates (see Table 1.03). For instance, high levels of repeat victimisation will be demonstrated by lower victimisation rates when compared with corresponding incidence rates as is found with domestic violence and vandalism (see for example, Chaplin et al., 2011).

______________________________________________________________________

10 See Section 2.5 of the User Guide for a discussion of repeat victimisation. 11 Where incidents of a similar nature that are probably carried out by the same perpetrator(s) have occurred, BCS estimates only include the first five incidents in this ‘series’ of victimisations, see Section 2.5 of the User Guide. Nearly one-third (31%) of the victims of hate crime were victimised more than once in the previous year and 18 per cent were victimised three or more times. This is similar to the extent of repeat victimisation for BCS crime overall (33% had been victimised more than once).

BCS figures have consistently shown that levels of repeat victimisation vary by offence type (Chaplin et al., 2011). One reason for this may be that victims are able to take more preventative measures against repeat victimisation for some crime types, such as theft from the person. It also reflects the different nature of offences.

It can be seen that hate crime was more likely to be repeatedly experienced for household crime offences than for personal crime offences; 37 per cent of victims of household hate crime had been victimised more than once in the previous year, compared with 19 per cent of victims of personal hate crime. This difference is larger than that found in the BCS overall (29% of victims of BCS household crime were repeat victims, compared with 21% of victims of BCS personal crime; Table 1.10).

1.5 REPORTING HATE CRIME

The BCS asks people who experienced crimes in the past year whether the police came to know about the incident, that is, whether they reported it or the police came to know about it in another way (for example, they arrived at the scene). A ‘reporting rate’ is calculated by dividing the number of BCS incidents that victims state the police came to know about by the total number of BCS incidents.

Based on the 2009/10 and 2010/11 BCS, the police were more likely to come to know about hate crime than BCS crime overall; 49 per cent of incidents of hate crime came to the attention of the police compared with 39 per cent of incidents of BCS crime overall (Table 1.11).

Although there was little difference in the likelihood of victims of personal hate crime reporting such offences to the police compared with all BCS personal crime (42% and 39% respectively), hate crime victims were more likely to report household crimes (59% compared with 40% for all BCS household crime). This difference could be due to the types and seriousness of offence recorded as hate crime. The 2010/11 BCS (Chaplin et al., 2011) showed that thefts of vehicles were most likely to be reported and incidents of burglary were also well reported.

Victims of crime who did not report incidents to the police were asked why they did not do so. The most frequently mentioned reason for not reporting hate crime incidents was that victims perceived them to be too trivial, there was no loss, or they believed that the police would or could not do much about them (55% of hate crime incidents that were not reported). The second most frequently mentioned reason was that it was a private matter or the victims chose to deal with it themselves (19% of unreported hate crimes).

Victims of hate crime were less likely than victims of BCS crime overall to say that the incident was too trivial to report to the police (55% compared with 73%). Conversely, they were more likely to give an answer from one of the less common categories grouped as ‘other’, for example something that happened as part of their job or someone else reported it (Table 1.12).

1.6 VICTIM SATISFACTION WITH THE POLICE

BCS respondents who were victims of crime and had contact with the police in the last 12 months were asked how satisfied they were with the way the police handled the matter. Based on the combined 2009/10 and 2010/11 surveys, in 53 per cent of incidents hate crime victims were satisfied with the way that the police handled the matter – in 33 per cent of incidents hate crime victims were very satisfied and in 21 per cent they were fairly satisfied with the way that the police handled the matter - and 45 per cent were not satisfied with the handling. Victims of hate crime were less satisfied with the way the police handled the matter than victims of BCS crime overall: in 53 per cent and 69 per cent of incidents respectively victims were satisfied (very or fairly) with the way the police handled the matter (Figure 1.1 and Table 1.13). In only 45 per cent of incidents of hate crime, victims thought the police took the matter as seriously as they should, compared with 65 per cent of incidents of BCS crime overall.

Victims of hate crime were less likely to think the police had treated them fairly or with respect, compared with victims of BCS crime overall. For example, in 63 per cent of hate crime incidents victims thought the police treated them fairly, compared with 79 per cent of incidents of BCS crime overall. Similarly, in 76 per cent of incidents of hate crime, victims thought the police treated them with respect, compared with 89 per cent of incidents of BCS crime overall (Table 1.13). 1.7 EFFECTS OF HATE CRIME

As part of the follow-up questions on their crime experience, victims were asked if they had an emotional reaction after the incident and, if so, how much they were affected and in which ways. There is evidence that perceiving that you have been targeted because of who you are has a greater impact on one’s wellbeing than being the victim of a non-hate crime (Iganski, 2001 and 2008).

Table 1.14 shows that victims of hate crime were more likely than victims of BCS crime overall to say they were emotionally affected by the incident (92% and 86% respectively) and more likely to be ‘very much’ affected (38% and 17% respectively).

Of those who said they were emotionally affected, victims of hate crimes gave the same types of emotions experienced by victims of BCS crime overall but (with the exception of annoyance) were more likely to mention each of them. In particular, 39 per cent of hate crime victims mentioned fear and 23 per cent mentioned anxiety, compared with 14 per cent and six per cent respectively of victims of BCS crime overall (Table 1.14).

Figure 1.2 Emotional impact of hate crime incident, 2009/10 and 2010/11 BCS 1.8 WORRY ABOUT HATE CRIME AND PERCEPTIONS OF THE LIKELIHOOD OF VICTIMISATION

The BCS provides estimates on a range of public perception measures relating to crime. The questions are shown in Box 1.2.12

Box 1.2 2009/10 and 2010/11 BCS questions (Perceptions of crime module)

The following question was asked of all respondents:

(How much of a problem is ...) people being attacked or harassed because of their skin colour, ethnic origin or religion?

- A very big problem
- A fairly big problem
- Not a very big problem
- Not a problem at all

The following questions were asked of a randomly selected one-quarter of respondents:

(How worried are you about) .....being subject to a physical attack because of your skin colour, ethnic origin or religion?

- Very worried
- Fairly worried
- Not very worried
- Not at all worried

And now, thinking about all types of crime, in general how worried are you about being a victim of crime?

- Very worried
- Fairly worried
- Not very worried
- Not at all worried

Do you think you are likely to be physically attacked or assaulted in the next year because of your skin colour, ethnic origin or religion?

- Yes
- No

Do you think you are likely to be harassed or intimidated in the next year because of your skin colour, ethnic origin or religion?

- Yes
- No

The BCS asks respondents about their perceived likelihood of being a victim of crime in the next 12 months. Overall, three per cent of adults thought they were ‘very’ or ‘fairly’ likely to be harassed because of their skin colour, ethnic origin or religion and two per cent said they were ‘very’ or ‘fairly’ likely to be attacked for these reasons. Adults from ethnic groups other than White were more likely than White adults to say they were ‘very’ or ‘fairly’ likely to be harassed (15% compared with 1% of White respondents) or attacked (10% compared with 1% of White respondents; Table 1.15).

There is a disparity between perceived likelihood and actual prevalence of crime. For example, ten per cent of respondents from Black and Minority Ethnic groups13 thought that they were ‘very’ or ‘fairly’ likely to be attacked because of their skin colour, ethnic origin or religion in the next 12 months,

12 See Section 6.2 of the User Guide for details of measures of likelihood of victimisation. 13 In the tables Black and Minority Ethnic groups are referred to as ‘Non-White’. compared with 0.7 per cent who reported having been a victim of racially motivated personal hate crime in the year before interview (Tables 1.15 and 1.06). This disparity is also found for other crime types, for example, burglary (14% of respondents thought that they were ‘very’ or ‘fairly’ likely to be a victim of burglary in the next 12 months, compared with 2% who reported having been a victim of burglary in the year before interview; Table 1.15, prevalence of burglary data not shown).

The BCS asks respondents how worried they are about being a victim of different types of crime. Overall, five per cent of adults were ‘very’ worried about being subject to a physical attack because of their skin colour, ethnic origin or religion, and, unsurprisingly, as with the other perception questions, this was much higher among adults from Black and Minority Ethnic backgrounds than among White adults (16% and 3% respectively; Table 1.15).

Six per cent of adults thought there was a ‘very’ or ‘fairly’ big problem in their area with people being attacked or harassed because of their skin colour, ethnic origin or religion. Adults from ethnic groups other than White were three times more likely to say there was a ‘very’ or ‘fairly’ big problem in their area than White adults (16% compared with 5% of White adults).

Figure 1.3 Perceptions of crime by ethnic group, 2009/10 and 2010/11 BCS 1.9 AGE AND GENDER-MOTIVATED HATE CRIME

The BCS also collects information on incidents that respondents perceive to be motivated by the offender’s attitude towards the victim’s age or gender. Estimates of age-motivated hate crime in particular should be treated with caution, as it is possible, for example, that older victims who may be targeted for their age-related vulnerability, are answering that the incident was motivated by the offender’s attitude towards their age rather than this vulnerability.

Table 1.16 outlines the number of incidents for which victims said that they thought the offender was motivated by attitude to their age or gender for the combined survey years 2009/10 and 2010/11. The number of incidents is the average per year over the two survey years.

In total, there were around 143,000 incidents of age-motivated hate crime a year, and around 0.3 per cent of people perceived they were victims of an age-motivated hate crime (Table 1.16).

There were around 120,000 incidents of gender-motivated hate crime a year, and around 0.2 per cent of adults were victims of a gender-motivated hate crime.

Table 1.17 shows the prevalence of age-motivated hate crime by age and sex. The youngest and oldest age groups were more likely to say they thought they had been a victim of age-motivated hate crime than other age groups (0.7% of those aged 16–24 and 0.6% of those aged 75 and over were victims of age-motivated hate crimes compared with 0.3% of those aged 65–74). This suggests that some people may have misunderstood or misheard the question and mistakenly be reporting an incident as age-motivated.

Women were more likely than men to say they were victims of gender-motivated hate crime (0.3% and 0.1% respectively; Table 1.18).

1.10 OTHER SOURCES OF HATE CRIME DATA

ACPO/Police data

The police have been recording reported hate crimes since 1 April 2008 for the five monitored strands of hate crime. Figures (covering England, Wales and Northern Ireland for 2009) were first published by the Association of Chief Police Officers (ACPO) in 2010, and figures for 2010 were published in September 2011. In 2011/12 the hate crime data collection was made part of the Home Office Annual Data Requirement.

Between January and December 2010, the police recorded 48,127 crimes in England, Wales and Northern Ireland where the victim, or any other person, perceived the criminal offence to be motivated by hostility based on a person’s race, religious belief, sexual orientation, disability or where the victim was perceived to be transgender.

Of these:

- 39,311 were racist crimes;
- 2,007 were religious (faith) hate crimes;
- 4,883 were based on sexual orientation;

14 http://www.acpo.presscentre.com/Press-Releases/ACPO-publishes-hate-crime-data-for-2010-111.aspx 15 The Annual Data Requirement (ADR) is a list of all requests made to all police forces in England and Wales under the Home Secretary’s statutory powers. 16 Data published per calendar year. • 357 targeted transgender people; and

• 1,569 targeted people with disabilities.

As expected, BCS hate crime estimates are higher than the number of hate crimes recorded by the police as the survey captures offences that are not reported to or recorded by the police.

Crown Prosecution Service data

In 2008, the CPS began publishing an annual report on Hate Crime in England and Wales. The most recent publication ‘Hate crime and crimes against older people report 2010–2011’ presents information on CPS performance in prosecuting racist and religious hate crime, transphobic and homophobic crime, and disability hate crime.17

The Life Opportunities Survey

In December 2011, the Office for Disability Issues published the Life Opportunities Survey Wave One results 2009/1118 based on a total of 31,161 interviews with adults aged 16 and over, across 19,951 households.

The survey found that two per cent of all adults interviewed had been a victim of hate crime in the past 12 months. This is higher than the BCS estimate of 0.5 per cent, partly because it includes age and gender-motivated hate crime but partly due to the different question wording.

Those who reported being a victim of hate crime were asked to select all motivations for the crime that applied to them from the following: age, sex, a health condition, illness or impairment, a disability, ethnicity, religion, sexual orientation, or none of these reasons. The most common motivation reported for all adults who experienced hate crime was ethnicity (37%) followed by sexual orientation (11%). It is important to note, however, that 34 per cent of adults with a mental or physical impairment and 30 per cent of adults without a mental or physical impairment gave the answer ‘none of these reasons’ to the question on motivation of hate crime and, thus, felt they were the victim of a hate crime motivated by factors not covered by the questionnaire.

17 http://www.cps.gov.uk/publications/docs/cps_hate_crime_report_2011.pdf 18 Office for Disability Issues (2011) Life Opportunities Survey: Wave One results, 2009/11. Available at: http://statistics.dwp.gov.uk/asd/asd1/los/los_wave_one_200911.pdf.

### Table 1.01 Number of incidents of hate crime and all BCS crime, by monitored strand

| Monitored strand of hate crime | Personal crime | Household crime | All crime | |-------------------------------|----------------|-----------------|-----------| | Race | 84 | 52 | 136 | | Religion | 21 | 19 | 39 | | Sexual orientation | 31 | 18 | 50 | | Disability | 29 | 35 | 65 | | Total hate crime | 151 | 109 | 260 | | Total BCS crime | 3,700 | 5,861 | 9,561 |

**Unweighted base**

| | 91,313 | 91,338 | 91,313 |

1. The numbers are derived by multiplying incidence rates by the population estimates for England and Wales, and are averaged over the two survey years. For more information see Section 2 of the User Guide.

2. Totals for hate crime might not be equal to the sum of incidents in the related equality strands as the victim may have said the crime was motivated by more than one strand. Excludes gender identity as questions on this strand were not included until 2011/12.

### Table 1.02 Incidence rate of hate crime and all BCS crime, by monitored strand

| Monitored strand of hate crime | Rates per 10,000 adults/households | |-------------------------------|-----------------------------------| | | Personal crime | Household crime | | Race | 19 | 22 | | Religion | 5 | 8 | | Sexual orientation | 7 | 8 | | Disability | 7 | 15 | | Total hate crime | 34 | 47 | | Total BCS crime | 827 | 2,510 |

**Unweighted base**

| | 91,313 | 91,338 |

1. Rates for personal crime are quoted per 10,000 adults. Rates for household crime are quoted per 10,000 households. The numbers are averaged over the two survey years.

2. Totals for hate crime might not be equal to the sum of incidents in the related equality strands as the victim may have said the crime was motivated by more than one strand. Excludes gender identity as questions on this strand were not included until 2011/12. Table 1.03 Proportion of adults and households who were victims of hate crime and all BCS crime, by monitored strand

| Monitored strand of hate crime | Personal crime | Household crime | All crime<sup>3</sup> | |-------------------------------|----------------|-----------------|----------------------| | Race | 0.2 | 0.1 | 0.3 | | Religion | 0.0 | 0.0 | 0.1 | | Sexual orientation | 0.0 | 0.0 | 0.1 | | Disability | 0.0 | 0.1 | 0.1 | | Total hate crime<sup>2</sup> | 0.2 | 0.2 | 0.5 | | Total BCS crime | 5.8 | 16.3 | 21.5 |

Unweighted base 91,313 91,338 91,313

1. Percentages for personal crime are based on adults. Percentages for household crime are based on households.
2. Totals for hate crime might not be equal to the sum of incidents in the related equality strands as the victim may have said the crime was motivated by more than one strand. Excludes gender identity as questions on this strand were not included until 2011/12.
3. This percentage is calculated treating a household crime as a personal crime. It is the estimated percentage of adults who have been a victim of at least one personal crime or have been resident in a household that was a victim of at least one household crime. Table 1.04 Proportion of adults who were victims of hate crime and all BCS crime, by personal characteristics Percentages

England and Wales, adults aged 16 and over, 2009/10 and 2010/11 BCS Personal hate All BCS personal All BCS crime Unweighted base All hate crime1,2 1 crime crime Percentage of adults/households victims once or more:

ALL ADULTS

0.2

0.5

5.8

21.5

91,313

16-24 25-34 35-44 45-54 55-64 65-74 75+

0.6 0.3 0.3 0.2 0.1 0.0 0.0

0.9 0.5 0.6 0.5 0.4 0.2 0.2

13.9 7.7 5.3 4.2 3.0 2.2 1.6

31.8 27.3 24.5 21.9 16.6 11.1 7.7

7,551 12,462 15,983 15,117 15,766 12,898 11,536

Men 16-24 25-34 35-44 45-54 55-64 65-74 75+

0.3 1.0 0.4 0.3 0.1 0.2 0.1 0.0

0.6 1.3 0.5 0.6 0.5 0.4 0.2 0.1

6.5 16.5 8.5 5.7 4.5 3.2 1.8 0.9

22.7 33.8 28.5 25.5 21.9 17.6 11.7 7.5

41,155 3,513 5,407 7,138 7,097 7,436 5,962 4,602

Women 16-24 25-34 35-44 45-54 55-64 65-74 75+

0.2 0.2 0.2 0.2 0.2 0.1 0.0 0.1

0.4 0.3 0.5 0.5 0.4 0.4 0.1 0.2

5.1 11.2 6.8 4.9 4.0 2.9 2.5 2.1

20.4 29.8 26.1 23.5 22.0 15.7 10.4 7.8

50,158 4,038 7,055 8,845 8,020 8,330 6,936 6,934

Ethnic group White Non-White Mixed Asian or Asian British Black or Black British Chinese or other

0.2 0.8 0.9 1.0 0.4 0.5

0.3 1.7 1.7 2.1 1.1 1.3

5.7 6.6 10.0 5.6 6.9 7.9

21.3 23.3 29.6 23.6 21.4 22.0

84,217 6,942 666 3,158 1,883 1,235

Religion Christian Buddhist Hindu Muslim Other No religion

0.2 1.3 0.8 1.0 0.6 0.3

0.3 1.5 1.8 2.1 1.3 0.4

4.3 5.1 4.3 5.6 7.3 7.4

19.8 25.8 21.2 23.1 27.0 27.1

69,854 408 897 2,167 1,142 16,596

Marital status Married Cohabiting Single Separated Divorced Widowed

0.1 0.1 0.6 0.3 0.3 0.1

0.3 0.4 0.9 0.5 0.7 0.3

3.3 6.2 11.6 7.7 5.9 2.7

18.7 26.6 28.1 24.5 21.4 9.8

42,711 8,133 18,900 2,975 8,305 10,260

Respondent's employment status In employment Unemployed Economically inactive Student Looking after family/home Long-term/temporarily sick/ill Retired Other inactive

0.2 0.8 0.2 0.6 0.1 0.7 0.1 0.7

0.4 1.1 0.5 0.8 0.4 2.0 0.2 1.1

6.3 11.2 4.4 13.6 4.0 6.3 2.0 6.3

24.1 28.8 16.5 30.5 22.0 24.9 10.2 23.2

49,530 2,837 38,717 2,230 4,774 4,019 26,385 1,309

Respondent's occupation Managerial and professional occupations Intermediate occupations Routine and manual occupations Never worked and long-term unemployed Full-time students Not classified

0.2 0.2 0.2 0.5 0.6 0.6

0.4 0.4 0.4 1.2 0.8 1.2

5.4 4.8 5.1 5.8 14.0 5.7

21.8 20.0 20.5 18.8 30.9 20.6

30,212 18,610 34,850 3,363 3,506 772

Highest qualification Degree or diploma Apprenticeship or A/AS level O level/GCSE Other None

0.3 0.3 0.3 0.3 0.2

0.4 0.4 0.6 0.5 0.5

6.1 7.3 6.8 4.2 3.5

23.3 24.3 23.8 16.8 15.4

29,744 15,473 17,601 3,987 24,300

Long-standing illness or disability Long-standing illness or disability Limits activities Does not limit activities No long-standing illness or disability

0.3 0.4 0.3 0.2

0.7 0.9 0.4 0.4

5.4 5.2 5.7 5.9

20.0 19.3 21.6 22.0

26,508 18,931 7,566 64,644

Hours out of home on an average weekday Less than 3 hours 3 hours less than 7 hours 7 hours or longer

0.2 0.2 0.3

0.4 0.5 0.5

3.2 5.6 7.3

15.0 21.2 25.1

27,421 24,994 38,717

Number of evening visits to bar in last month None Less than once a week Once a week or more often

0.2 0.2 0.3

0.6 0.3 0.4

4.1 6.0 9.1

18.4 23.1 26.4

47,190 25,685 18,426

Number of visits to a nightclub in last month None Less than once a week Once a week or more often

0.2 0.4 1.0

0.4 0.7 1.0

4.7 12.4 19.2

19.9 31.2 39.7

83,362 6,477 1,466

1. Excludes gender identity as questions on this strand were not included until 2011/12.
2. This percentage is calculated treating a household crime as a personal crime. It is the estimated percentage of adults who have been a victim of at least one personal crime or have been resident in a household that was a victim of at least one household crime.
3. See Section 7.3 of the User Guide for definitions of personal characteristics.

29

Table 1.05 Proportion of adults and households who were victims of hate crime and all BCS crime, by household and area characteristics

| Percentages | England and Wales, adults aged 16 and over, 2009/10 and 2010/11 BCS | |-------------|---------------------------------------------------------------------| | | Personal hate crime¹ | Household hate crime¹ | All hate crime² | All BCS personal crime | All BCS household crime | All BCS crime | Unweighted base | | ALL HOUSEHOLDS | 0.2 | 0.2 | 0.5 | 5.8 | 16.3 | 21.5 | 91,313 | | Structure of household | | | | | | | | | Single adult & child(ren) | 0.2 | 0.3 | 0.6 | 9.0 | 24.3 | 30.1 | 4,710 | | Adults & child(ren) | 0.3 | 0.3 | 0.5 | 6.0 | 21.6 | 25.8 | 19,597 | | Adult(s) & no children | 0.2 | 0.2 | 0.5 | 5.6 | 14.3 | 19.5 | 67,006 | | Total household income | | | | | | | | | Less than £10,000 | 0.5 | 0.5 | 1.0 | 6.3 | 14.5 | 19.8 | 12,877 | | £10,000 less than £20,000 | 0.3 | 0.4 | 0.7 | 5.0 | 14.8 | 19.2 | 18,038 | | £20,000 less than £30,000 | 0.2 | 0.1 | 0.3 | 5.2 | 17.6 | 21.8 | 12,533 | | £30,000 less than £40,000 | 0.2 | 0.2 | 0.3 | 5.0 | 17.8 | 21.6 | 9,305 | | £40,000 less than £50,000 | 0.2 | 0.1 | 0.3 | 6.1 | 19.2 | 23.9 | 6,200 | | £50,000 or more | 0.1 | 0.1 | 0.2 | 6.3 | 20.7 | 25.9 | 12,410 | | No income stated or not enough information provided | 0.2 | 0.3 | 0.5 | 6.2 | 13.7 | 20.0 | 19,847 | | Tenure | | | | | | | | | Owners | 0.2 | 0.2 | 0.3 | 4.4 | 15.4 | 19.7 | 62,059 | | Social renters | 0.4 | 0.6 | 1.0 | 7.1 | 17.4 | 23.4 | 15,211 | | Private renters | 0.4 | 0.2 | 0.5 | 9.5 | 18.6 | 26.1 | 13,715 | | Accommodation type | | | | | | | | | Houses | 0.2 | 0.2 | 0.4 | 5.5 | 16.5 | 21.4 | 77,886 | | Detached | 0.1 | 0.1 | 0.2 | 4.0 | 13.1 | 17.0 | 23,974 | | Semi-detached | 0.2 | 0.2 | 0.4 | 5.4 | 15.6 | 20.7 | 29,063 | | Terraced | 0.4 | 0.3 | 0.7 | 6.8 | 20.3 | 26.0 | 24,849 | | Flats/maisonettes | 0.4 | 0.4 | 0.7 | 8.2 | 15.7 | 22.7 | 11,680 | | Other accommodation | 0.2 | 0.3 | 0.2 | 0.7 | 5.1 | 4.6 | 255 | | Output Area Classification | | | | | | | | | Blue collar communities | 0.2 | 0.3 | 0.5 | 6.2 | 18.8 | 23.9 | 15,412 | | City living | 0.3 | 0.3 | 0.5 | 8.4 | 18.0 | 25.7 | 4,256 | | Countryside | 0.1 | 0.1 | 0.2 | 4.1 | 10.7 | 14.7 | 14,000 | | Prospering suburbs | 0.1 | 0.1 | 0.2 | 4.4 | 12.9 | 17.3 | 21,793 | | Constrained by circumstances | 0.3 | 0.3 | 0.6 | 5.9 | 17.2 | 23.0 | 9,200 | | Typical traits | 0.2 | 0.2 | 0.4 | 5.5 | 18.6 | 23.7 | 18,858 | | Multicultural | 0.6 | 0.6 | 1.2 | 8.7 | 19.5 | 26.2 | 7,784 | | Area type | | | | | | | | | Urban | 0.3 | 0.3 | 0.6 | 6.2 | 17.5 | 23.1 | 68,006 | | Rural | 0.1 | 0.1 | 0.2 | 4.1 | 11.6 | 15.5 | 23,307 | | Level of physical disorder | | | | | | | | | High | 0.6 | 0.7 | 1.3 | 6.8 | 23.1 | 27.9 | 4,605 | | Not high | 0.2 | 0.2 | 0.4 | 5.7 | 15.9 | 21.1 | 85,539 | | English Indices of Deprivation (Employment) | | | | | | | | | 20% most deprived output areas | 0.4 | 0.5 | 0.8 | 6.6 | 18.9 | 24.3 | 15,930 | | Other output areas | 0.2 | 0.2 | 0.5 | 5.8 | 16.4 | 21.8 | 50,463 | | 20% least deprived output areas | 0.2 | 0.1 | 0.3 | 5.3 | 14.0 | 19.0 | 17,160 |

1. Excludes gender identity as questions on this strand were not included until 2011/12.
2. This percentage is calculated treating a household crime as a personal crime. It is the estimated percentage of adults who have been a victim of at least one personal crime or have been resident in a household that was a victim of at least one household crime.
3. See Sections 7.1 and 7.2 of the User Guide for definitions of area and household characteristics. Table 1.06 Proportion of adults who were victims of racially-motivated hate crime, by ethnic group

| Percentages | England and Wales, adults aged 16 and over, 2009/10 and 2010/11 BCS | |-------------|---------------------------------------------------------------------| | | Personal racially-motivated hate crime | All racially-motivated hate crime | Unweighted base | | | % victims once or more: | % victims once or more: | | | ALL ADULTS | 0.2 | 0.3 | 91,313 | | Ethnic group| | | | | White | 0.1 | 0.1 | 84,217 | | Non-White | 0.7 | 1.4 | 6,942 | | Mixed | 0.7 | 1.1 | 666 | | Asian or Asian British | 0.9 | 1.8 | 3,158 | | Black or Black British | 0.4 | 0.9 | 1,883 | | Chinese or other | 0.4 | 1.1 | 1,235 |

1. This percentage is calculated treating a household crime as a personal crime. It is the estimated percentage of adults who have been a victim of at least one personal crime or have been resident in a household that was a victim of at least one household crime. Table 1.07 Proportion of adults who were victims of religion-motivated hate crime, by ethnic group and religion

| Percentages | England and Wales, adults aged 16 and over, 2009/10 and 2010/11 BCS | |-------------|---------------------------------------------------------------------| | | Personal religion-motivated hate crime | All religion-motivated hate crime | Unweighted base | | | % victims once or more: | % victims once or more: | | | ALL ADULTS | 0.0 | 0.1 | 91,313 | | Ethnic group| | | | | White | 0.0 | 0.0 | 84,217 | | Non-White | 0.2 | 0.5 | 6,942 | | Mixed | 0.1 | 0.1 | 666 | | Asian or Asian British | 0.4 | 0.8 | 3,158 | | Black or Black British | 0.0 | 0.2 | 1,883 | | Chinese or other | 0.0 | 0.1 | 1,235 | | Religion | | | | | Christian | 0.0 | 0.0 | 69,854 | | Buddhist | 0.0 | 0.0 | 408 | | Hindu | 0.0 | 0.5 | 897 | | Muslim | 0.5 | 0.8 | 2,167 | | Other | 0.1 | 0.7 | 1,142 | | No religion | 0.0 | 0.0 | 16,596 |

1. This percentage is calculated treating a household crime as a personal crime. It is the estimated percentage of adults who have been a victim of at least one personal crime or have been resident in a household that was a victim of at least one household crime.

Table 1.08 Proportion of adults who were victims of sexual-orientation-motivated hate crime, by age and sex

| Percentages | England and Wales, adults aged 16 and over, 2009/10 and 2010/11 BCS | |-------------|---------------------------------------------------------------------| | | Personal sexual-orientation-motivated hate crime | All sexual orientation-motivated hate crime | Unweighted base | | | % victims once or more | % victims once or more | | | ALL ADULTS | 0.0 | 0.1 | 91,313 | | 16-24 | 0.1 | 0.2 | 7,551 | | 25-34 | 0.0 | 0.0 | 12,462 | | 35-44 | 0.1 | 0.1 | 15,983 | | 45-54 | 0.0 | 0.1 | 15,117 | | 55-64 | 0.0 | 0.1 | 15,766 | | 65-74 | 0.0 | 0.0 | 12,898 | | 75+ | 0.0 | 0.0 | 11,536 | | Men | 0.1 | 0.1 | 41,155 | | Women | 0.0 | 0.1 | 50,158 |

1. This percentage is calculated treating a household crime as a personal crime. It is the estimated percentage of adults who have been a victim of at least one personal crime or have been resident in a household that was a victim of at least one household crime. Table 1.09 Proportion of adults who were victims of disability-motivated hate crime, by employment status and presence of long-standing illness or disability

| Percentages | England and Wales, adults aged 16 and over, 2009/10 and 2010/11 BCS | |-------------|---------------------------------------------------------------------| | | Personal disability-motivated hate crime | All disability-motivated hate crime | Unweighted base | | | % victims once or more | % victims once or more | % victims once or more | | ALL ADULTS | 0.0 | 0.1 | 91,313 |

**Respondent’s employment status**

| Employment status | Personal disability-motivated hate crime | All disability-motivated hate crime | Unweighted base | |-------------------|------------------------------------------|------------------------------------|-----------------| | In employment | 0.0 | 0.0 | 49,530 | | Unemployed | 0.1 | 0.1 | 2,837 | | Economically inactive | 0.1 | 0.2 | 38,717 | | Student | 0.1 | 0.1 | 2,230 | | Looking after family/home | 0.0 | 0.1 | 4,774 | | Long-term/temporarily sick/ill | 0.5 | 1.3 | 4,019 | | Retired | 0.0 | 0.1 | 26,385 | | Other inactive | 0.2 | 0.3 | 1,309 |

**Long-standing illness or disability**

| Presence of long-standing illness or disability | Personal disability-motivated hate crime | All disability-motivated hate crime | Unweighted base | |-------------------------------------------------|------------------------------------------|------------------------------------|-----------------| | Long-standing illness or disability | 0.1 | 0.4 | 26,508 | | Limits activities | 0.2 | 0.5 | 18,931 | | Does not limit activities | 0.0 | 0.1 | 7,566 | | No long-standing illness or disability | 0.0 | 0.0 | 64,644 |

1. This percentage is calculated treating a household crime as a personal crime. It is the estimated percentage of adults who have been a victim of at least one personal crime or have been resident in a household that was a victim of at least one household crime.

Table 1.10 Number of times victims were victimised in previous year

| Percentages | England and Wales, adults aged 16 and over, 2009/10 and 2010/11 BCS | |-------------|---------------------------------------------------------------------| | | Once | Twice | Three or more | Unweighted base | | Personal hate crime | 81 | 8 | 11 | 185 | | All BCS personal crime | 79 | 12 | 10 | 4,505 | | Household hate crime | 63 | 15 | 22 | 207 | | All BCS household crime | 71 | 18 | 12 | 14,385 | | All hate crime | 69 | 13 | 18 | 379 | | All BCS crime | 67 | 18 | 14 | 17,522 |

1. Base is victims of specified offences.
2. Excludes gender identity as questions on this strand were not included until 2011/12.

### Table 1.11 Proportion of BCS crime incidents reported to the police

| Percentages | England and Wales, adults aged 16 and over, 2009/10 and 2010/11 BCS | Unweighted base | |-------------|---------------------------------------------------------------|-----------------| | | Incident reported to police | | | Personal hate crime | 42 | 195 | | All BCS personal crime | 39 | 5,138 | | Household hate crime | 59 | 237 | | All BCS household crime | 40 | 17,784 | | All hate crime | 49 | 432 | | All BCS crime | 39 | 22,922 |

1. Incidents that were reported to the police also includes those incidents that the police came to know about in another way, e.g. they arrived at the scene.
2. Base is crime incidents.
3. Excludes gender identity as questions on this strand were not included until 2011/12.

### Table 1.12 Reasons for not reporting crime incident to the police

| Percentages | England and Wales, adults aged 16 and over, 2009/10 and 2010/11 BCS | All hate crime | All BCS crime | |-------------|---------------------------------------------------------------|---------------|---------------| | Trivial/no loss/police would not/could not do anything | 55 | 73 | | Private/dealt with ourselves | 19 | 15 | | Inconvenient to report | 6 | 6 | | Reported to other authorities | 4 | 5 | | Common occurrence | 9 | 3 | | Fear of reprisal | 5 | 2 | | Dislike or fear of the police/previous bad experience with the police or courts | 7 | 2 | | Other | 21 | 6 |

Unweighted base | 195 | 12,912 |

1. Excludes gender identity as questions on this strand were not included until 2011/12.
2. The answer categories 'Too trivial/not worth reporting', 'No loss/damage', 'Police would not have been bothered/interested', 'Police could not do anything' and 'Attempt at offence was unsuccessful' are merged due to the similarity in their definition, for example: a respondent who thinks the incident was too trivial may code the incident as 'too trivial, no loss' or 'the police would not be interested' as these two codes may be understood as meaning the same.
3. This category includes: something that happens as part of job; partly my/friend's/relative's fault; offender not responsible for actions; thought someone else had reported incident/similar incidents; tried to report but was not able to contact the police/police not interested; other.
4. Base is crime incidents not reported to police.
5. Figures may add to more than 100 as more than one reason could be given.

### Table 1.13 Satisfaction with police handling of crime incidents

| Victim satisfaction | All hate crime | All BCS crime | |-------------------------------------|----------------|---------------| | Very satisfied | 33 | 37 | | Fairly satisfied | 21 | 32 | | A bit dissatisfied | 22 | 16 | | Very dissatisfied | 23 | 14 | | Too early to say | 2 | 1 | | % saying police took matter as seriously as they should | 45 | 65 |

| Police treated victim fairly | | | |-------------------------------------|----------------|---------------| | Yes | 63 | 79 | | Not entirely | 21 | 13 | | Not at all | 15 | 8 |

| Police treated victim with respect | | | |-------------------------------------|----------------|---------------| | Yes | 76 | 89 | | Not entirely | 14 | 7 | | Not at all | 10 | 4 |

Unweighted base: 223 8,863

1. Excludes gender identity as questions on this strand were not included until 2011/12.
2. Base is crime incidents that were reported to police.

### Table 1.14 Emotional impact of crime incident

| Respondent was emotionally affected | All hate crime | All BCS crime | |-------------------------------------|----------------|---------------| | Very much | 38 | 17 | | Quite a lot | 31 | 26 | | Just a little | 23 | 43 | | Respondent was not emotionally affected | 8 | 14 |

Unweighted base: 420 22,065

### Type of emotional response experienced

| Type of emotional response experienced | All hate crime | All BCS crime | |---------------------------------------|----------------|---------------| | Anger | 67 | 60 | | Annoyance | 50 | 60 | | Shock | 40 | 28 | | Loss of confidence or feeling vulnerable | 35 | 15 | | Fear | 39 | 14 | | Anxiety or panic attacks | 23 | 6 | | Crying/tears | 13 | 9 | | Difficulty sleeping | 17 | 8 | | Depression | 20 | 6 | | Other | 3 | 3 |

Unweighted base: 383 19,028

1. Excludes gender identity as questions on this strand were not included until 2011/12.
2. Figures add to more than 100 as more than one response possible. Table 1.15 Perceptions of racially-motivated hate crime, by ethnic group

| Percentages | White | All Non-White | Mixed | Asian or Asian British | Black or Black British | Chinese or other | All adults | |-------------|-------|---------------|-------|------------------------|------------------------|------------------|-----------| | Perceived likelihood of being victim of racially-motivated crime | | | | | | | | | 'Very' or 'fairly' likely to be attacked because of skin colour/ethnic origin/religion | 1 | 10 | 4 | 12 | 9 | 9 | 2 | | 'Very' or 'fairly' likely to be harassed because of skin colour/ethnic origin/religion | 1 | 15 | 13 | 17 | 12 | 11 | 3 | | 'Very' or 'fairly' likely to be burgled | 13 | 25 | 19 | 29 | 20 | 20 | 14 | | Worry about of being victim of crime | | | | | | | | | 'Very' worried about being attacked because of skin colour/ethnic origin/religion | 3 | 16 | 14 | 16 | 16 | 13 | 5 | | 'Very' worried about being a victim of any crime | 6 | 18 | 21 | 18 | 18 | 16 | 7 | | Unweighted base | 20,745 | 1,638 | 143 | 777 | 436 | 282 | 22,402 | | Problem of racially-motivated crime | | | | | | | | | in their area with racially-motivated hate crime | 5 | 16 | 16 | 18 | 14 | 14 | 6 | | Unweighted base | 82,870 | 6,840 | 655 | 3,133 | 1,842 | 1,210 | 89,851 |

1. Questions on worry about crime and the likelihood of attack and harassment were only asked of one-quarter of the BCS sample.

### Table 1.16 Age- and gender-motivated hate crime

| | Personal crime | Household crime | All crime | |----------------------|----------------|-----------------|-----------| | **Age-motivated hate crime** | | | | | Incidents of hate crime (numbers, 000s) | 95 | 48 | 143 | | Incidence rates per 10,000 adults/households | 21 | 21 | * | | Percentage victims once or more | 0.2 | 0.1 | 0.3 | | **Gender-motivated hate crime** | | | | | Incidents of hate crime (numbers, 000s) | 90 | 30 | 120 | | Incidence rates per 10,000 adults/households | 20 | 13 | * | | Percentage victims once or more | 0.2 | 0.1 | 0.2 |

**Unweighted base**

| | 91,313 | 91,338 | 91,313 |

1. The numbers are derived by multiplying incidence rates by the population estimates for England and Wales, and are averaged over the two survey years.
2. Rates for personal crime are quoted per 10,000 adults. Rates for household crime are quoted per 10,000 households.
3. Percentages for personal crime are based on adults. Percentages for household crime are based on households.

- It is not possible to construct a rate for all BCS crime because rates for household offences are based on rates per household, and those for personal offences on rates per adult, and the two cannot be combined. Table 1.17 Proportion of adults who were victims of age-motivated hate crime, by age and sex

| Percentages | England and Wales, adults aged 16 and over, 2009/10 and 2010/11 BCS | |-------------|---------------------------------------------------------------------| | | Personal age-motivated hate crime | All age-motivated hate crime | Unweighted base | | | % victims once or more: | | | | ALL ADULTS | 0.2 | 0.3 | 91,313 | | 16-24 | 0.6 | 0.7 | 7,551 | | 25-34 | 0.1 | 0.2 | 12,462 | | 35-44 | 0.1 | 0.1 | 15,983 | | 45-54 | 0.0 | 0.1 | 15,117 | | 55-64 | 0.1 | 0.2 | 15,766 | | 65-74 | 0.2 | 0.3 | 12,898 | | 75+ | 0.3 | 0.6 | 11,536 | | Men | 0.2 | 0.3 | 41,155 | | 16-24 | 0.9 | 1.0 | 3,513 | | 25-34 | 0.1 | 0.2 | 5,407 | | 35-44 | 0.0 | 0.1 | 7,138 | | 45-54 | 0.0 | 0.1 | 7,097 | | 55-64 | 0.1 | 0.2 | 7,436 | | 65-74 | 0.1 | 0.3 | 5,962 | | 75+ | 0.2 | 0.4 | 4,602 | | Women | 0.2 | 0.3 | 50,158 | | 16-24 | 0.4 | 0.5 | 4,038 | | 25-34 | 0.0 | 0.1 | 7,055 | | 35-44 | 0.1 | 0.1 | 8,845 | | 45-54 | 0.0 | 0.1 | 8,020 | | 55-64 | 0.1 | 0.2 | 8,330 | | 65-74 | 0.2 | 0.3 | 6,936 | | 75+ | 0.4 | 0.7 | 6,934 |

1. This percentage is calculated treating a household crime as a personal crime. It is the estimated percentage of adults who have been a victim of at least one personal crime or have been resident in a household that was a victim of at least one household crime. Table 1.18 Proportion of adults who were victims of gender-motivated hate crime by age and sex

| Percentages | England and Wales, adults aged 16 and over, 2009/10 and 2010/11 BCS | |-------------|---------------------------------------------------------------------| | | Personal gender-motivated hate crime | All gender-motivated hate crime | Unweighted base | | | % victims once or more: | | | | ALL ADULTS | 0.2 | 0.2 | 91,313 | | 16-24 | 0.3 | 0.4 | 7,551 | | 25-34 | 0.3 | 0.4 | 12,462 | | 35-44 | 0.2 | 0.2 | 15,983 | | 45-54 | 0.0 | 0.1 | 15,117 | | 55-64 | 0.0 | 0.1 | 15,766 | | 65-74 | 0.0 | 0.0 | 12,898 | | 75+ | 0.0 | 0.0 | 11,536 | | Men | 0.1 | 0.1 | 41,155 | | 16-24 | 0.1 | 0.1 | 3,513 | | 25-34 | 0.2 | 0.2 | 5,407 | | 35-44 | 0.1 | 0.1 | 7,138 | | 45-54 | 0.0 | 0.1 | 7,097 | | 55-64 | 0.0 | 0.1 | 7,436 | | 65-74 | 0.0 | 0.0 | 5,962 | | 75+ | 0.0 | 0.0 | 4,602 | | Women | 0.2 | 0.3 | 50,158 | | 16-24 | 0.6 | 0.7 | 4,038 | | 25-34 | 0.5 | 0.7 | 7,055 | | 35-44 | 0.2 | 0.3 | 8,845 | | 45-54 | 0.1 | 0.2 | 8,020 | | 55-64 | 0.1 | 0.2 | 8,330 | | 65-74 | 0.0 | 0.1 | 6,936 | | 75+ | 0.1 | 0.1 | 6,934 |

1. This percentage is calculated treating a household crime as a personal crime. It is the estimated percentage of adults who have been a victim of at least one personal crime or have been resident in a household that was a victim of at least one household crime. 2 Use of the internet and cyber security

Jacqueline Hoare

2.1 SUMMARY

This chapter contains information from the 2010/11 British Crime Survey (BCS) on levels of internet use, concerns people may have about using the internet, and any measures taken to protect personal details when using the internet. Questions were asked of adults aged 16 or over in England and Wales. Headline findings are summarised below and interesting variations by age and sex are highlighted throughout the chapter.

Internet usage

According to the 2010/11 BCS, 78 per cent of adults had used the internet in the last year; men were more likely than women to have done so (81% and 75% respectively). Levels of usage decreased with increasing age, from 98 per cent of 16 to 24 year olds to 19 per cent of those aged 75 or older.

Among adults who had used the internet in the last year, the most commonly reported use was for emailing, instant messaging or visiting chat rooms (83% of internet users). Around three-quarters (77%) said they used the internet for buying goods or services online and 73 per cent to browse for news or homework. Half (50%) of adults said they used the internet for online government services.

Protection of personal details

Among adults who said they had used the internet for any of the three online activities of interest (buying goods or services, online banking or managing finances and online government services), level of worry about the security of the personal details entered online varied as follows:

- Of adults who said they used the internet for buying goods or services, 44 per cent said they were worried and just over a third of adults (37%) who reported using the internet for banking or managing finances were worried.

- Around a quarter of adults (26%) who said they had used the internet for government services were worried about their personal details being secure online, the lowest among users of each of these internet services.

The most commonly mentioned actions taken by adults to protect their personal details online were: having up-to-date security software installed on home computer (67%), using only well-known, popular or trusted sites (67%), and using secure sites (such as indicated by a closed padlock, 61%).

Perceived barriers to use

The main reason given by adults who said they had not used the internet for each of the three online activities of interest (buying goods or services, online banking or managing finances and online government services) was that there was no need to (36%, 33% and 53% respectively).

Concern about personal details being insecure was given as a reason that had stopped people using the internet most commonly for online banking or managing finances (34%), then for buying goods or services (26%) and then for accessing online government services (10%).

Concern about losing money or having money stolen was given as a reason by 16 per cent of adults in relation to stopping them accessing online banking or managing finances, then for buying goods or services (12%) and less commonly for online government services (3%). 2.2 INTRODUCTION

In November 2011 the Government published the UK Cyber Security Strategy(^1) which focuses on all risks relating to internet use. By 2015, the Government’s aspiration is that the measures outlined in the strategy will mean the UK is in a position where law enforcement is tackling cyber criminals, citizens know what to do to protect themselves, effective cyber security is seen as a positive for UK business, a thriving cyber security sector has been established, public services online are secure and resilient, and the threats to national infrastructure and national security have been confronted.

Since 2008/09, the British Crime Survey (BCS) has asked adults about their internet use and from 2010/11 it has also asked about perceived barriers to using the internet for any of three online activities of interest (buying goods or services, online banking or managing finances and online government services) and worry about the security of personal details when using the internet. Questions were also asked about any negative online experiences (such as a computer virus or loss of money) and measures taken to protect personal details when using the internet, relating to the ‘citizens know what to do to protect themselves’ element of the UK Cyber Security Strategy.

Details of the questions asked in 2010/11 are shown in Boxes 2.1 to 2.5 of this chapter. Further question development has taken place for the 2012/13 survey to add an additional focus on different ways of accessing the internet and on understanding why people take the measures they do to keep safe online (see Box 2.6; these data will be available from summer 2013).

The figures published here are based on the questions relating to internet use that were first asked in the 2010/11 BCS. As data from only one year are presented, it is not possible to make comparisons with earlier survey years.

2.3 LEVELS OF INTERNET USE

According to the 2010/11 BCS, 78 per cent of adults had used the internet (at home or elsewhere) in the 12 months prior to interview.(^2) Men were more likely than women to have done so (81% and 75% respectively; Table 2.01).

As would be expected, levels of internet use decreased with increasing age, from 98 per cent of 16 to 24 year olds to 19 per cent of those aged 75 or older. Levels of use were similar for men and women in each age group between the ages of 16 to 64 (for example, 95% of men aged 25 to 34 and 94% of women aged 25 to 34). In the older age groups, however, men were significantly more likely to have used the internet in the last year than women:

- Just over half (53%) of men aged 65 to 74 had used the internet in the last year, higher than the two in five women in the 65 to 74 age group (39%).

- Men aged 75 or older were twice as likely as women in the same age range to have used the internet in the last year (27% and 13% respectively).

It is these differences in levels of internet use among those aged 65 or over that explain the overall difference that can be seen in internet usage between men (81%) and women (75%).

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1. [http://www.cabinetoffice.gov.uk/resource-library/cyber-security-strategy](http://www.cabinetoffice.gov.uk/resource-library/cyber-security-strategy)
2. This figure corresponds closely with the 77 per cent of the UK population who had used the internet in the three months prior to a 2010 interview according to the National Statistics Omnibus survey ([http://www.ons.gov.uk/ons/rel/rdit2/internet-access-households-and-individuals/2010/index.html](http://www.ons.gov.uk/ons/rel/rdit2/internet-access-households-and-individuals/2010/index.html)). Frequency of internet use

Of the 78 per cent of adults who accessed the internet in the last year, nine in ten had used the internet more than once a week (91%) with around eight in ten (78%) having used it every day or almost every day (Table 2.02). This equates to around 71 per cent of all adults aged 16 or over having used the internet more than once a week in the last year and around 61 per cent having used it every day or almost every day (data not shown).

Among internet users, men (79%) were more likely than women (76%) to have used the internet on a daily or almost daily basis. As shown previously for usage overall, this difference can be largely explained by the disparity in frequency of usage among the older age groups, for example:

- Sixty-two per cent of men aged 75 or over who used the internet in the last year used it every day or almost every day, significantly higher than the 43 per cent of women in the same age group.

2.4 WHAT THE INTERNET IS USED FOR

Adults who had used the internet in the last year were asked what types of activities they had used the internet for, from a limited choice shown to them on a card (see Box 2.1). Only two per cent of adults said they did not use the internet for any of these activities.

The most commonly reported use was for emailing, instant messaging or visiting chat rooms (83% of internet users). Around three-quarters (77%) said they used the internet for buying goods or services online (this includes internet shopping and music/film downloads) and 73 per cent to browse for news or homework. Half (50%) of adults said they used the internet for online government services (such as tax returns, activities relating to the DVLA, or benefits; Figure 2.1 and Table 2.03).

Among those that only used the internet for one activity (9%) it was most likely to be browsing for news or homework (31%) and least likely to be using online government services (1%; data not shown).

For most types of internet use (buying goods or services, browsing for news or homework, online banking or managing finances, online government services) the peak in levels of use (generally for 25 to 34 year olds) was followed by decreases with increasing age. For example (Figure 2.2):

- Seventy-two per cent of 25 to 34 year olds who used the internet in the last year had done so for online banking, falling to 38 per cent of those aged 75 or over. Figure 2.1 Types of activities that the internet is used for among internet users aged 16 and over, 2010/11 BCS

1. Not all internet activities are shown here as adults were given a choice of responses from a card (see Box 2.1).

Figure 2.2 Variation by age in use of activities among internet users aged 16 and over, 2010/11 BCS However, among adults who used the internet for emailing, instant messaging or visiting chat rooms (83% of internet users) the decline for older adults was less evident. There was a peak in levels of use for those aged 25 to 34 (87%), falling only to 81 per cent of those aged 75 or over.

Again, the pattern of use by age was different for adults using the internet for social networking (57% of internet users). This type of internet activity was most common for adults aged 16 to 24 (89%) compared with all other types of activity (e.g. 78% for emailing or instant messaging) and compared with all older age groups:

- There was a sharp decline in the proportion of adults who used the internet for social networking from those aged 16 to 24 (89%) to those aged 75 or over (12%).

The analysis that follows focuses on the three key activities which are now part of the UK Cyber Security Strategy: buying goods or services, online banking or managing finances and online government services.

Buying goods or services online was the most common (77%) of the three online activities of interest. Similar proportions of men and women used the internet for buying goods or services (78% and 76% respectively) and this activity was most likely to be done by internet-using adults aged 25 to 44 (25 to 34: 83%; 35 to 44: 82%).

Online banking or managing finances was an activity reported by 58 per cent of internet users. However, there was some variation by age and sex. Men (61%) were more likely to use the internet for banking or managing finances than women (55%).

As previously described, adults aged 25 to 34 (72%) were the most likely to use online banking or financial management compared with all other age groups, falling with increasing age to 38 per cent of those aged 75 or over. This finding by age holds true for each sex:

- There were statistically significantly higher proportions of men aged 25 to 34 and women aged 25 to 34 (74% and 69% respectively) who had used the internet for online banking compared with all other age groups within sex.

Half of internet-using adults (50%) accessed government services online (such as for tax returns); men were more likely to do so than women (55% compared with 45%). The youngest (16 to 24 year olds; 29%) and oldest (75 or over; 36%) age groups were least likely to use online government services with levels of use being generally similar among adults aged between 25 and 64 years old.

### 2.5 WORRY ABOUT SECURITY OF PERSONAL DETAILS

Adults who said they had used the internet for any of the three online activities of interest (buying goods or services, online banking or managing finances and online government services) were asked a follow-up question after each to gauge their level of worry about the security of personal details entered online (see Box 2.2 and Table 2.04).

- Of adults who said they used the internet for buying goods or services, 44 per cent said they were worried about the security of the personal details they had entered online (7% were ‘very’ worried and the remaining 37% were ‘fairly’ worried).

- Just over a third of adults (37%) who reported using the internet for banking or managing finances were worried about the security of their personal details when doing so; only seven per cent were ‘very’ worried.

- Around a quarter of adults (26%) who said they had used the internet for government services were worried about their personal details being secure online, the lowest among users of each of these internet services. While not directly comparable, levels of worry about the security of personal details entered online appeared higher than for estimates of worry about other crime types from the BCS, for example, ten per cent of adults were worried about being a victim of burglary (Chaplin et al., 2011). However, levels of worry were lower than worry about being a victim of plastic card fraud (53% of plastic card owners, Moon et al., 2010).

However, it is worth noting that overall between a half and three-quarters of internet users were not worried about the security of their personal details entered online when using the internet for the specified activities; that is, 56 per cent of adults who had used the internet for buying goods or services, 63 per cent who used online banking and 74 per cent who had used online government services.

There were some variations in levels of worry when considering personal characteristics, although fewer differences than found elsewhere in this chapter. Among those who had used the internet for buying goods or services, women were more likely than men to be worried about the security of their personal details online (46% and 42% respectively; Table 2.05).

It was clear that among adults who had used the internet to buy goods or services, those aged 16 to 24 were the least likely to be worried about the security of their personal details entered online (32%, compared with 51% of 45 to 54 year olds for example). While 16 to 24 year olds were not the highest online consumers of goods or services, seven in ten (71%) internet users said they did use the internet to buy goods or services. Of those that did, two-thirds (68%) were not worried about the security of personal details online.

### 2.6 PROTECTING PERSONAL DETAILS

Adults who had used the internet in the last year were asked whether or not they had taken certain measures to protect personal details online (see Box 2.3).

Nearly everyone who used the internet reported that they had adopted at least one of the measures asked about. Only three per cent said they did nothing to protect their personal details as they were not worried about security. Of the actions asked about, the most commonly mentioned were (Figure 2.3 and Table 2.06):

- Two-thirds of adults who had used the internet in the last year (67%) reported that they had up-to-date security software installed on a home computer.(^3)

- Two-thirds (67%) said they only used well-known or popular or trusted sites.

- Three in five (61%) said they looked for secure sites (such as a closed padlock system).

**Figure 2.3 Proportion of internet users aged 16 and over taking measures to protect personal details online, 2010/11 BCS**

There were no statistically significant differences between men and women in the proportion who took the three most common actions, although there were some differences by age:

- Adults aged 75 or over were less likely to report having up-to-date security software installed than all younger age groups (53% compared with 67% of those aged 65 to 74 for example).

- People in the oldest age group were also least likely to have said they only used well-known or popular or trusted sites (52% compared with, for example, 66% of those aged 16 to 24).

- Adults aged 75 or over (45%) were generally less likely to look for secure sites than most younger age groups (for example, 65% of 45 to 54 year olds); however, the youngest adults aged 16 to 24 (54%) were generally less likely than older groups to look for secure sites (for example, 64% of 25 to 34 year olds).

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3 Respondents were not asked specifically whether they had a home computer hence some of the 33 per cent who did not say they had security software installed may be accounted for by those that did not have a home computer and therefore could not have security software installed. Adults who used the internet most frequently were more likely to carry out the three most common actions:

- Compared with adults who had used the internet once a week or less, adults who had used the internet more than once a week were twice as likely to have installed up-to-date security software on a home computer (35% and 70% respectively) and to have looked for secure sites (32% and 64% respectively).

- Adults who had used the internet more than once a week were also more likely to have said they only used well-known or popular or trusted sites (69%) compared with those using the internet less frequently (41%).

Around a quarter (27%) of adults who had used the internet in the last year said they did not put personal details online as a precautionary measure; those aged 55 or over were most likely to do this (for example, 42% of those aged 75 or over).

### 2.7 PERCEIVED BARRIERS TO INTERNET USE

Adults who said they had not used the internet for each of the three online activities of interest (buying goods or services, online banking or managing finances and online government services) were asked a follow-up question to see if there was anything that had stopped them doing so (see Box 2.4).

The main reason given by adults for not using the internet for these activities was that there was no need to (Tables 2.07a to 2.07c):

- Around a third of internet-using adults said there was no need to use the internet for buying goods or services (36%) or for online banking or financial management (33%).

______________________________________________________________________

4 Frequency of internet use was shown to be associated with experience of a computer virus in the last year (see Section 2.7); hence figures presented here show that frequent users were more likely to both have security software installed and also to have experienced a computer virus. However, it is not possible to say anything about the quality of the software installed or whether the software was installed before or after the computer virus was experienced. • Just over half of adults (53%) reported that there was no need to use online government services.

This reason was generally given as a response irrespective of age and sex; however, young people aged 16 to 24 were more likely than any other age group to say there was no need to use the internet for online banking or managing finances (52%, compared with 34% of 25 to 34 year olds, for example) or for online government services (64%, compared with 54% of those aged 25 to 34, for example).

Box 2.4 2010/11 BCS question (internet use module)

The following question was asked of respondents who said they had not used the internet for online banking or managing finances, for buying goods or services or for online government services:

In the last 12 months is there anything that has stopped you using the Internet for [this activity]? (Respondents were asked to respond without any prompts from the interviewer):

• Lack of interest • No need • Lack of confidence/skills • No computer or access • Cannot afford it • Feel too old • Concern about my personal details being insecure • Concern about losing money/having money stolen

Concern about personal details being insecure was given as a reason that had stopped people using the internet most commonly for online banking or managing finances (34%), then for buying goods or services (26%) and then for accessing online government services (10%).

Concern about losing money or having money stolen was a reason given by 16 per cent of adults in relation to stopping them accessing online banking or managing finances (the third most common reason for this activity), then for buying goods or services (12%) and less commonly for online government services (3%).

The proportion of internet users who were concerned about losing money or having money stolen was lower in relation to each of the three activities than concern about personal details being insecure; this is interesting because the loss of personal details is often associated with subsequent loss of money. Also, it may reflect that the financial loss tends to be borne by the financial institution (rather than victims) when money is taken from a bank account or credit card.

For each of the three activities it was clear that those in the youngest age group were least likely to give the reasons of being concerned about personal details being insecure or losing/having money stolen as barriers to internet usage compared with most of the older age groups. For example:

• Concern about personal details being insecure was given as a reason for not using the internet for buying goods or services by 11 per cent of 16 to 24 year olds, significantly lower than all older age groups (for example, 36% of those aged 75 or over).

• Internet users aged 75 or over were five times as likely (25%) as those aged 16 to 24 (5%) to report that concern about losing money or having money stolen was a reason for not using online banking or managing finances. Three per cent of those aged 16 to 24 who had used the internet in the last year but not for online government services reported that concern about personal details being insecure was a reason for not doing so, lower than the 20 per cent of adults aged 75 or over who gave the same reason.

Part of the UK Cyber Security Strategy includes ‘The need for everyone to have the ability – in terms of skills, technology, confidence and opportunity – to access cyberspace’. Figures from the 2010/11 BCS showed that (Tables 2.07a to 2.07c):

- Lack of confidence or skills was reported as a reason stopping them using the internet for buying goods or services by five per cent of internet-using adults who did not use the internet for this activity. The equivalent figures for online banking or managing finances and online government services were seven and four per cent respectively.

- Among internet users who did not use the internet for each of the three activities, only very low proportions gave no computer or access to a computer as a reason stopping them from accessing goods or services, banking or financial management or government services online (2%, 1% and 1% respectively).

Although still a low proportion, women were more likely than men to say that lack of confidence or skills was a reason stopping them from using online banking or managing finances (8% and 6% respectively) or online government services (5% and 3% respectively).

Adults aged 16 to 34 who had not used the internet for buying goods or services were least likely to say that lack of confidence or skills was a reason stopping them using the internet for this activity (16 to 24 year olds: 1%; 25 to 34 year olds: 2%; compared with 13% of adults aged 65 to 74 for example).

Although there were some patterns in the data that suggested variation on barriers to internet use by age, these were not all statistically significant. This may in part be due to the small numbers of people responding to these questions when broken down by age group; small numbers will affect the tests of significance hence any real differences may not be detected.

### 2.8 NEGATIVE EXPERIENCES WHILE USING THE INTERNET

Adults who had used the internet in the last year were asked whether or not they had experienced certain types of negative behaviours or actions as a result of using the internet (see Box 2.5). This question is an indicator but not a measure of cyber-enabled crimes as the experiences asked about may or may not have been criminal.

**Box 2.5 2010/11 BCS question (internet use module)**

*Respondents who said they had used the internet in the year prior to interview were asked:*

In the last 12 months, have you personally experienced any of the things mentioned on this card while using the internet? (Respondents were asked to choose all options that applied from a card they were shown):

- A computer virus
- Loss of money
- Unauthorised access to/use of personal data (e.g. email account, bank account)
- Upsetting images/illegal images
- Abusive/ threatening behaviour
- None of these Three in five adults (61%) said that they had not experienced any of these negative behaviours or actions; of those asked about, the most commonly cited was a computer virus which had been experienced by a third of internet-using adults (33%) in the last year. Six per cent of adults reported that someone had unauthorised access to or had used their personal data (for example, their email or bank account) and three per cent said they had lost money while using the internet (Tables 2a and 2.08).

Table 2a Negative experiences in the last year among internet users aged 16 and over

| Percentages | A computer virus | Unauthorised access to use of personal data | Upsetting/illegal images | Loss of money | Abusive/threatening behaviour | None of these | Unweighted base | |-------------|-----------------|------------------------------------------|-------------------------|--------------|-------------------------------|--------------|----------------| | All internet users | 33 | 6 | 4 | 3 | 2 | 61 | 8,383 |

1. Base is the quarter-sample of the 2010/11 BCS who were asked questions about internet use who said they had used the internet in the last year.

Focusing on the most common experience, there were clear differences in likelihood of experiencing a computer virus in the last year: this had been experienced by more men (38%) than women (29%) and by those in the youngest age group more than all other age groups (43% of 16 to 24 year olds compared with, for example, 34% of 25 to 34 year olds; Figure 2.4). In particular, young men aged 16 to 24 were the most likely to have experienced a computer virus in the last year (48%, higher than all other ages of men and also women).

Figure 2.4 Proportion of internet users aged 16 and over who experienced a computer virus in the last 12 months by age, sex and internet usage, 2010/11 BCS Unsurprisingly, frequency of internet use was associated with experience of a computer virus in the last year. Adults who used the internet more than once a week were twice as likely to have had a computer virus as those using the internet once a week or less (35% and 17% respectively).\\textsuperscript{5}

\\textsuperscript{5} Further analysis of these data suggests that the relationship between frequency of use and experience of a computer virus holds true irrespective of age. Box 2.6 2012/13 BCS questions about internet use

The module of questions reported on in this chapter continues to be asked in the 2011/12 BCS. Amendments have been made for the 2012/13 survey to include the following questions:

Respondents who said they had used the internet in the year prior to interview will be asked:

Which of these have you used in the last 12 months to access the internet? (Respondents will be asked to choose all options that apply from a card they are shown):

- Desktop computer (at home or work)
- Laptop (at home or work)
- Laptop (away from home or work)
- Mobile phone or smartphone
- Handheld computer (e.g. iPad, tablet, palmtop)
- Games console
- Digital TV
- Other

The following question is an amended version of a question reported on in this chapter. It asks respondents more generally about keeping safe online (rather than focusing solely on protecting personal details):

Which of these things do you do to keep yourself safe online, including protecting your personal details on the internet? (Respondents will be asked to choose all options that apply from a card they are shown):

- Only use well-known/popular/trusted sites
- Look for a secure site (closed padlock system/https://website address)
- Do not use public wi-fi/insecure wi-fi
- Password protect own internet network (broadband, wi-fi)
- Password protect device used to access the internet (laptop, computer, phone)
- Have up-to-date security software on home computer
- Only use credit cards (not debit or charge cards)
- Do not put personal details online
- Other
- Nothing – not worried about security

The following question will be asked of respondents who said they took any precautions at the previous question:

What are the main reasons, if any, that you take this/these precautions to keep yourself safe online? (Respondents will be asked to choose all options that apply from a card they are shown):

- Advice from family/friend/someone else
- Advertising by/advice from government
- Advice from police/crime prevention officer
- Media reports in newspapers/on TV/in other media
- Have had computer virus in the past
- Have lost money online in the past
- Have had personal details accessed without permission in the past
- Have received upsetting/illegal images in the past
- Generally aware about risks of using the internet
- Other reason
- No particular reason Table 2.01 Proportion of adults using the internet in the last year, by age and sex

| Percentages | England and Wales, adults aged 16 and over, 2010/11 BCS | |-------------|--------------------------------------------------------| | | Unweighted base 1 | | ALL ADULTS | 78 11,666 | | 16-24 | 98 983 | | 25-34 | 95 1,580 | | 35-44 | 92 2,034 | | 45-54 | 85 1,975 | | 55-64 | 72 2,000 | | 65-74 | 46 1,666 | | 75+ | 19 1,428 | | Men | 81 5,217 | | 16-24 | 98 433 | | 25-34 | 95 696 | | 35-44 | 93 932 | | 45-54 | 86 916 | | 55-64 | 74 920 | | 65-74 | 53 758 | | 75+ | 27 562 | | Women | 75 6,449 | | 16-24 | 98 550 | | 25-34 | 94 884 | | 35-44 | 92 1,102 | | 45-54 | 84 1,059 | | 55-64 | 71 1,080 | | 65-74 | 39 908 | | 75+ | 13 866 |

1. Base is the quarter-sample of the 2010/11 BCS who were asked questions about internet use.
2. See Section 7.3 of the User Guide for definitions of personal characteristics. Table 2.02 Frequency of internet use among adults who used the internet in the last year, by age and sex

| Percentages | More than once a week | Every day/almost every day | Two or three times a week | Once a week or less often | Once a week | Less than once a week | Unweighted base | |-------------|-----------------------|---------------------------|--------------------------|--------------------------|------------|----------------------|----------------| | ALL INTERNET USERS | 91 | 78 | 14 | 9 | 5 | 4 | 8,382 | | 16-24 | 94 | 84 | 11 | 6 | 3 | 2 | 953 | | 25-34 | 94 | 84 | 9 | 6 | 3 | 3 | 1,498 | | 35-44 | 93 | 80 | 13 | 7 | 4 | 3 | 1,889 | | 45-54 | 90 | 75 | 14 | 10 | 6 | 5 | 1,659 | | 55-64 | 86 | 68 | 18 | 14 | 6 | 8 | 1,393 | | 65-74 | 84 | 63 | 21 | 16 | 7 | 9 | 735 | | 75+ | 80 | 54 | 26 | 20 | 10 | 10 | 255 | | Men | 92 | 79 | 13 | 8 | 4 | 4 | 3,891 | | 16-24 | 94 | 83 | 11 | 6 | 4 | 2 | 426 | | 25-34 | 95 | 86 | 9 | 5 | 2 | 3 | 662 | | 35-44 | 94 | 82 | 12 | 6 | 4 | 2 | 867 | | 45-54 | 91 | 77 | 14 | 9 | 5 | 4 | 767 | | 55-64 | 87 | 70 | 17 | 13 | 6 | 7 | 646 | | 65-74 | 88 | 68 | 20 | 12 | 5 | 7 | 384 | | 75+ | 82 | 62 | 20 | 18 | 11 | 7 | 139 | | Women | 90 | 76 | 14 | 10 | 5 | 5 | 4,491 | | 16-24 | 95 | 85 | 10 | 5 | 3 | 2 | 527 | | 25-34 | 93 | 83 | 10 | 7 | 5 | 2 | 836 | | 35-44 | 93 | 79 | 14 | 7 | 4 | 3 | 1,022 | | 45-54 | 89 | 74 | 15 | 11 | 6 | 5 | 892 | | 55-64 | 84 | 65 | 19 | 16 | 6 | 9 | 747 | | 65-74 | 78 | 57 | 22 | 22 | 10 | 11 | 351 | | 75+ | 76 | 43 | 34 | 24 | 10 | 14 | 116 |

1. Base is the quarter-sample of the 2010/11 BCS who were asked questions about internet use who said they had used the internet in the last year.
2. See Section 7.3 of the User Guide for definitions of personal characteristics.

### Table 2.03 Internet activities among adults who used the internet in the last year, by age, sex and internet usage

| Percentages | Email, instant messaging, chat rooms | Buying goods or services | Browsing for news or homework | Online banking or managing finances | Social networking | Online government services | None of these | Unweighted base | |-------------|-------------------------------------|-------------------------|-------------------------------|-----------------------------------|------------------|---------------------------|--------------|-----------------| | **ALL INTERNET USERS** | 83 | 77 | 73 | 58 | 57 | 50 | 2 | 8,383 | | 16-24 | 78 | 71 | 70 | 48 | 89 | 29 | 1 | 953 | | 25-34 | 87 | 83 | 77 | 72 | 76 | 56 | 1 | 1,498 | | 35-44 | 84 | 82 | 79 | 64 | 62 | 58 | 1 | 1,890 | | 45-54 | 82 | 78 | 76 | 57 | 41 | 56 | 2 | 1,659 | | 55-64 | 81 | 72 | 68 | 50 | 25 | 53 | 3 | 1,393 | | 65-74 | 84 | 68 | 63 | 49 | 15 | 49 | 4 | 735 | | 75+ | 81 | 59 | 64 | 38 | 12 | 36 | 5 | 255 | | **Men** | 83 | 78 | 77 | 61 | 55 | 55 | 2 | 3,891 | | 16-24 | 79 | 71 | 75 | 49 | 87 | 32 | 2 | 426 | | 25-34 | 87 | 84 | 80 | 74 | 74 | 61 | 1 | 662 | | 35-44 | 84 | 82 | 82 | 67 | 60 | 62 | 1 | 867 | | 45-54 | 81 | 80 | 80 | 60 | 40 | 62 | 2 | 767 | | 55-64 | 81 | 73 | 70 | 54 | 22 | 58 | 3 | 646 | | 65-74 | 84 | 70 | 67 | 54 | 16 | 59 | 5 | 384 | | 75+ | 78 | 65 | 66 | 45 | 12 | 41 | 5 | 139 | | **Women** | 83 | 76 | 70 | 55 | 58 | 45 | 2 | 4,492 | | 16-24 | 78 | 70 | 65 | 48 | 90 | 25 | 0 | 527 | | 25-34 | 87 | 82 | 74 | 69 | 78 | 52 | 0 | 836 | | 35-44 | 83 | 83 | 76 | 61 | 64 | 54 | 1 | 1,023 | | 45-54 | 82 | 76 | 72 | 54 | 41 | 50 | 2 | 892 | | 55-64 | 81 | 72 | 66 | 46 | 28 | 48 | 4 | 747 | | 65-74 | 84 | 66 | 58 | 42 | 14 | 36 | 3 | 351 | | 75+ | 85 | 51 | 61 | 29 | 11 | 28 | 5 | 116 |

**Internet usage**

| | More than once a week | Once a week or less often | |-----------------|------------------------|---------------------------| | **Men** | 87 | 38 | | **Women** | 80 | 39 |

1. Base is the quarter-sample of the 2010/11 BCS who were asked questions about internet use who said they had used the internet in the last year.
2. See Section 7.3 of the User Guide for definitions of personal characteristics. Table 2.04 Proportion of adults who had used the internet in the last year for each activity who were worried about the security of personal details entered online for that activity

| Percentages | England and Wales, internet users aged 16 and over, 2010/11 BCS | |-------------|---------------------------------------------------------------| | | Buying goods or services | Online banking or managing finances | Online government services | | Worried | 44 | 37 | 26 | | Very worried| 7 | 7 | 5 | | Fairly worried| 37 | 30 | 21 | | Not worried | 56 | 63 | 74 | | Not very worried| 44 | 46 | 52 | | Not at all worried| 12 | 17 | 23 |

Unweighted base ¹ 6,414 4,807 4,308

¹. Base is the quarter-sample of the 2010/11 BCS who were asked questions about internet use who said they had used the internet in the last year and for each of these activities. Table 2.05 Proportion of adults who had used the internet in the last year for each activity who were worried about the security of personal details entered online for that activity, by age, sex and internet usage

| Percentages | Buying goods or services | Online banking or managing finances | Online government services | |-------------|--------------------------|-------------------------------------|---------------------------| | | Unweighted base¹ | Unweighted base¹ | Unweighted base¹ | | ALL INTERNET USERS | 44 | 6,414 | 37 | 4,807 | 26 | 4,308 | | 16-24 | 32 | 671 | 31 | 459 | 22 | 268 | | 25-34 | 43 | 1,244 | 35 | 1,055 | 21 | 852 | | 35-44 | 44 | 1,548 | 35 | 1,209 | 26 | 1,103 | | 45-54 | 51 | 1,292 | 42 | 949 | 29 | 920 | | 55-64 | 50 | 1,020 | 45 | 694 | 31 | 738 | | 65-74 | 48 | 496 | 40 | 347 | 26 | 341 | | 75+ | 47 | 143 | 28 | 94 | 20 | 86 | | Men | 42 | 3,013 | 36 | 2,349 | 25 | 2,219 | | 16-24 | 28 | 300 | 31 | 203 | 21 | 133 | | 25-34 | 42 | 561 | 37 | 490 | 23 | 416 | | 35-44 | 41 | 705 | 33 | 578 | 25 | 540 | | 45-54 | 51 | 612 | 40 | 473 | 26 | 475 | | 55-64 | 47 | 477 | 39 | 349 | 29 | 386 | | 65-74 | 46 | 271 | 42 | 195 | 24 | 215 | | 75+ | 47 | 87 | 31 | 61 | 27 | 54 | | Women | 46 | 3,401 | 38 | 2,458 | 27 | 2,089 | | 16-24 | 36 | 371 | 30 | 256 | 23 | 135 | | 25-34 | 43 | 683 | 33 | 565 | 19 | 436 | | 35-44 | 47 | 843 | 37 | 631 | 27 | 563 | | 45-54 | 52 | 680 | 44 | 476 | 32 | 445 | | 55-64 | 53 | 543 | 51 | 345 | 34 | 352 | | 65-74 | 50 | 225 | 38 | 152 | 29 | 126 | | 75+ | 46 | 56 | 21 | 33 | 6 | 32 | | Internet usage | | | | | | | | More than once a week | 44 | 6,075 | 37 | 4,646 | 26 | 4,171 | | Once a week or less often | 52 | 339 | 38 | 161 | 30 | 137 |

1. Base is the quarter-sample of the 2010/11 BCS who were asked questions about internet use who said they had used the internet in the last year and for each of these activities.
2. See Section 7.3 of the User Guide for definitions of personal characteristics.

### Table 2.06 Measures taken by adults who used the internet in the last year to protect personal details online, by age, sex and internet usage

| Percentages | Installed up-to-date security software on home computer | Only use well-known/popular/trusted sites | Look for secure sites | Always keep copy of web page/order form/correspondence | Only order from companies that are based in UK | Do not put personal details online | Only use credit cards (not debit/charge cards) | Only use sites that are professionally designed | Only buy from new sites recommended by established companies | Some other security measure | Nothing - not worried about security | Unweighted base | |-------------|--------------------------------------------------------|------------------------------------------|----------------------|--------------------------------------------------------|-----------------------------------------------|----------------------------------------|------------------------------------------|-------------------------------------------------|-------------------------------------------------|-----------------------------------------------|-----------------------------------------------|-----------------| | **ALL INTERNET USERS** | 67 | 67 | 61 | 39 | 30 | 27 | 25 | 15 | 12 | 1 | 3 | 8,382 | | 16-24 | 61 | 66 | 54 | 24 | 26 | 25 | 6 | 18 | 14 | 1 | 5 | 953 | | 25-34 | 66 | 66 | 64 | 40 | 28 | 23 | 21 | 18 | 13 | 2 | 3 | 1,497 | | 35-44 | 69 | 71 | 67 | 45 | 32 | 24 | 29 | 15 | 13 | 1 | 3 | 1,890 | | 45-54 | 69 | 68 | 65 | 45 | 30 | 26 | 33 | 13 | 12 | 2 | 3 | 1,659 | | 55-64 | 68 | 63 | 58 | 44 | 33 | 35 | 38 | 12 | 10 | 2 | 2 | 1,393 | | 65-74 | 67 | 62 | 53 | 38 | 38 | 35 | 35 | 14 | 10 | 1 | 3 | 735 | | 75+ | 53 | 52 | 45 | 29 | 34 | 31 | 12 | 9 | 1 | 4 | 255 | | **Men** | 68 | 66 | 61 | 37 | 30 | 26 | 26 | 17 | 13 | 2 | 4 | 3,890 | | 16-24 | 61 | 65 | 57 | 24 | 26 | 22 | 8 | 20 | 15 | 1 | 7 | 426 | | 25-34 | 66 | 65 | 63 | 39 | 28 | 22 | 20 | 20 | 14 | 2 | 3 | 661 | | 35-44 | 72 | 70 | 65 | 41 | 29 | 25 | 30 | 16 | 13 | 2 | 4 | 867 | | 45-54 | 70 | 66 | 66 | 40 | 31 | 26 | 34 | 14 | 12 | 2 | 3 | 787 | | 55-64 | 70 | 61 | 58 | 40 | 32 | 32 | 35 | 14 | 12 | 2 | 2 | 646 | | 65-74 | 71 | 66 | 56 | 41 | 41 | 36 | 36 | 16 | 10 | 0 | 3 | 384 | | 75+ | 54 | 53 | 47 | 30 | 35 | 41 | 32 | 15 | 9 | 2 | 2 | 139 | | **Women** | 65 | 67 | 61 | 42 | 30 | 28 | 25 | 14 | 12 | 1 | 3 | 4,492 | | 16-24 | 62 | 67 | 50 | 25 | 25 | 29 | 5 | 17 | 12 | 1 | 2 | 527 | | 25-34 | 66 | 67 | 65 | 41 | 28 | 23 | 21 | 15 | 13 | 1 | 4 | 836 | | 35-44 | 67 | 71 | 69 | 49 | 34 | 23 | 28 | 14 | 13 | 1 | 3 | 1,023 | | 45-54 | 68 | 69 | 64 | 49 | 30 | 26 | 32 | 12 | 12 | 1 | 3 | 892 | | 55-64 | 66 | 65 | 59 | 47 | 34 | 37 | 41 | 11 | 8 | 1 | 2 | 747 | | 65-74 | 63 | 58 | 49 | 34 | 35 | 35 | 33 | 11 | 10 | 1 | 3 | 351 | | 75+ | 51 | 51 | 44 | 29 | 32 | 44 | 29 | 8 | 9 | 0 | 6 | 116 | | **Internet usage** | | | | | | | | | | | | | | More than once a week | 70 | 69 | 64 | 42 | 32 | 26 | 27 | 16 | 13 | 1 | 3 | 7,541 | | Once a week or less often | 35 | 41 | 32 | 13 | 12 | 39 | 12 | 6 | 7 | 3 | 11 | 840 |

1. Base is the quarter-sample of the 2010/11 BCS who were asked questions about internet use who said they had used the internet in the last year.
2. See Section 7.3 of the User Guide for definitions of personal characteristics. Table 2.07a Reasons for not using the internet for buying goods or services among adults who used the internet in the last year, by age, sex and internet usage

| Percentages | No need | Concern about personal details being insecure | Lack of interest | Concern about losing money/having money stolen | Lack of confidence/skills | No computer or access to computer | Cannot afford it | Feel too old | None of these | Unweighted base | |-------------|---------|-----------------------------------------------|------------------|-----------------------------------------------|--------------------------|----------------------------------|----------------|-------------|--------------|----------------| | ALL INTERNET USERS | 36 | 26 | 14 | 12 | 5 | 2 | 1 | 1 | 20 | 1,966 | | 16-24 | 45 | 11 | 13 | 7 | 1 | 1 | 2 | 0 | 29 | 282 | | 25-34 | 45 | 23 | 14 | 9 | 2 | 1 | 1 | 0 | 20 | 252 | | 35-44 | 35 | 29 | 12 | 8 | 4 | 2 | 2 | 0 | 19 | 342 | | 45-54 | 31 | 29 | 16 | 14 | 7 | 2 | 1 | 0 | 17 | 366 | | 55-64 | 27 | 34 | 15 | 20 | 8 | 2 | 1 | 3 | 18 | 373 | | 65-74 | 29 | 37 | 13 | 17 | 13 | 2 | 0 | 1 | 11 | 239 | | 75+ | 30 | 36 | 16 | 15 | 11 | 3 | 1 | 3 | 13 | 112 | | Men | 38 | 25 | 14 | 10 | 4 | 2 | 1 | 0 | 22 | 877 | | 16-24 | 43 | 8 | 14 | 2 | 1 | 0 | 0 | 0 | 36 | 126 | | 25-34 | 52 | 23 | 11 | 8 | 1 | 0 | 1 | 0 | 17 | 100 | | 35-44 | 34 | 29 | 13 | 6 | 3 | 3 | 1 | 0 | 20 | 162 | | 45-54 | 33 | 29 | 17 | 12 | 6 | 1 | 0 | 0 | 19 | 155 | | 55-64 | 35 | 29 | 15 | 17 | 5 | 3 | 1 | 0 | 21 | 169 | | 65-74 | 27 | 40 | 12 | 19 | 13 | 2 | 0 | 0 | 10 | 113 | | 75+ | 27 | 44 | 15 | 13 | 7 | 4 | 1 | 3 | 9 | 52 | | Women | 34 | 26 | 14 | 14 | 6 | 1 | 2 | 1 | 18 | 1,089 | | 16-24 | 46 | 13 | 12 | 12 | 1 | 2 | 4 | 0 | 23 | 156 | | 25-34 | 38 | 23 | 17 | 11 | 3 | 2 | 2 | 0 | 23 | 152 | | 35-44 | 37 | 29 | 11 | 9 | 6 | 1 | 3 | 0 | 17 | 180 | | 45-54 | 30 | 29 | 16 | 15 | 9 | 2 | 1 | 0 | 16 | 211 | | 55-64 | 18 | 39 | 15 | 23 | 11 | 1 | 1 | 5 | 15 | 204 | | 65-74 | 30 | 33 | 14 | 15 | 13 | 2 | 0 | 2 | 13 | 126 | | 75+ | 32 | 28 | 18 | 16 | 14 | 3 | 0 | 2 | 16 | 60 | | Internet usage | | | | | | | | | | | | More than once a week | 37 | 28 | 12 | 13 | 4 | 1 | 1 | 1 | 20 | 1,465 | | Once a week or less often | 34 | 28 | 12 | 13 | 4 | 1 | 1 | 1 | 19 | 500 |

1. Base is the quarter-sample of the 2010/11 BCS who were asked questions about internet use who said they had used the internet in the last year but not for buying goods or services.
2. See Section 7.3 of the User Guide for definitions of personal characteristics. Table 2.07b Reasons for not using the internet for online banking or managing finances among adults who used the internet in the last year, by age, sex and internet usage

| Percentages | Concern about personal details being insecure | No need | Concern about losing money/having money stolen | Lack of interest | Lack of confidence/skills | No computer or access to computer | Feel too old | Cannot afford it | None of these | Unweighted base | |-------------|-----------------------------------------------|---------|-----------------------------------------------|-----------------|--------------------------|-----------------------------------|-------------|-----------------|--------------|----------------| | ALL ADULTS | 34 | 33 | 16 | 11 | 7 | 1 | 0 | 0 | 18 | 3,574 | | 16-24 | 11 | 52 | 5 | 9 | 3 | 1 | 0 | 0 | 26 | 494 | | 25-34 | 32 | 34 | 16 | 12 | 5 | 2 | 0 | 0 | 21 | 442 | | 35-44 | 37 | 27 | 17 | 12 | 7 | 1 | 0 | 1 | 17 | 681 | | 45-54 | 41 | 26 | 20 | 12 | 8 | 2 | 0 | 0 | 16 | 709 | | 55-64 | 43 | 27 | 23 | 11 | 9 | 1 | 2 | 0 | 14 | 699 | | 65-74 | 47 | 26 | 21 | 10 | 10 | 1 | 1 | 0 | 11 | 388 | | 75+ | 51 | 25 | 25 | 12 | 11 | 2 | 3 | 0 | 6 | 161 | | Men | 33 | 34 | 16 | 12 | 6 | 1 | 0 | 0 | 19 | 1,542 | | 16-24 | 10 | 50 | 4 | 13 | 0 | 1 | 0 | 0 | 30 | 223 | | 25-34 | 31 | 36 | 16 | 11 | 7 | 2 | 0 | 1 | 20 | 172 | | 35-44 | 38 | 29 | 17 | 12 | 7 | 2 | 0 | 1 | 16 | 289 | | 45-54 | 41 | 27 | 20 | 11 | 7 | 1 | 0 | 0 | 16 | 294 | | 55-64 | 40 | 30 | 22 | 12 | 8 | 2 | 1 | 0 | 13 | 237 | | 65-74 | 52 | 24 | 24 | 14 | 8 | 1 | 0 | 0 | 11 | 189 | | 75+ | 50 | 22 | 25 | 12 | 7 | 2 | 3 | 1 | 7 | 78 | | Women | 34 | 33 | 16 | 10 | 8 | 1 | 1 | 0 | 18 | 2,032 | | 16-24 | 13 | 55 | 6 | 5 | 5 | 1 | 0 | 1 | 22 | 271 | | 25-34 | 34 | 33 | 17 | 13 | 4 | 2 | 0 | 0 | 21 | 270 | | 35-44 | 37 | 26 | 17 | 12 | 8 | 1 | 0 | 1 | 18 | 392 | | 45-54 | 42 | 26 | 20 | 12 | 9 | 3 | 0 | 0 | 16 | 415 | | 55-64 | 45 | 25 | 23 | 9 | 10 | 1 | 2 | 0 | 16 | 402 | | 65-74 | 43 | 28 | 18 | 7 | 13 | 1 | 2 | 0 | 11 | 199 | | 75+ | 51 | 27 | 24 | 12 | 15 | 1 | 3 | 0 | 5 | 83 | | Internet usage | More than once a week | 35 | 33 | 17 | 9 | 6 | 1 | 0 | 0 | 18 | 2,894 | | | Once a week or less often | 29 | 34 | 13 | 18 | 11 | 4 | 1 | 1 | 17 | 679 |

1. Base is the quarter-sample of the 2010/11 BCS who were asked questions about internet use who said they had used the internet in the last year but not for online banking or managing finances.
2. See Section 7.3 of the User Guide for definitions of personal characteristics. Table 2.07c Reasons for not using the internet for online government services among adults who used the internet in the last year, by age, sex and internet usage

| Percentages | No need | Concern about personal details being insecure | Lack of confidence/skills | Concern about losing money/having money stolen | No computer or access to computer | Cannot afford it | Feel too old | None of these | Unweighted base | |-------------|---------|-----------------------------------------------|---------------------------|-----------------------------------------------|---------------------------------|-----------------|-------------|--------------|----------------| | ALL ADULTS | 53 | 10 | 10 | 4 | 3 | 1 | 0 | 0 | 23 | 4,071 | | 16-24 | 64 | 3 | 7 | 2 | 1 | 1 | 0 | 0 | 26 | 683 | | 25-34 | 54 | 8 | 12 | 2 | 2 | 2 | 0 | 0 | 25 | 645 | | 35-44 | 51 | 14 | 8 | 4 | 3 | 1 | 1 | 0 | 24 | 787 | | 45-54 | 47 | 14 | 13 | 7 | 3 | 1 | 0 | 0 | 22 | 739 | | 55-64 | 48 | 16 | 11 | 7 | 4 | 1 | 0 | 1 | 22 | 654 | | 65-74 | 44 | 14 | 12 | 10 | 5 | 2 | 0 | 1 | 20 | 394 | | 75+ | 44 | 20 | 7 | 10 | 4 | 2 | 1 | 3 | 19 | 169 | | Men | 53 | 11 | 11 | 3 | 2 | 2 | 0 | 0 | 23 | 1,671 | | 16-24 | 63 | 2 | 9 | 0 | 1 | 1 | 0 | 0 | 26 | 292 | | 25-34 | 56 | 7 | 13 | 2 | 2 | 3 | 0 | 0 | 22 | 246 | | 35-44 | 53 | 14 | 9 | 4 | 2 | 2 | 1 | 0 | 21 | 327 | | 45-54 | 46 | 17 | 13 | 6 | 3 | 1 | 0 | 0 | 21 | 292 | | 55-64 | 48 | 17 | 12 | 5 | 4 | 1 | 0 | 0 | 22 | 260 | | 65-74 | 37 | 18 | 13 | 9 | 4 | 2 | 0 | 1 | 22 | 169 | | 75+ | 47 | 20 | 7 | 3 | 3 | 2 | 1 | 4 | 20 | 85 | | Women | 53 | 10 | 9 | 5 | 3 | 1 | 0 | 0 | 24 | 2,400 | | 16-24 | 64 | 3 | 6 | 3 | 2 | 1 | 0 | 0 | 25 | 391 | | 25-34 | 53 | 10 | 10 | 1 | 2 | 1 | 0 | 0 | 27 | 399 | | 35-44 | 49 | 13 | 8 | 4 | 4 | 1 | 0 | 0 | 26 | 460 | | 45-54 | 49 | 12 | 12 | 7 | 3 | 2 | 0 | 0 | 22 | 447 | | 55-64 | 48 | 14 | 11 | 9 | 5 | 1 | 0 | 3 | 22 | 394 | | 65-74 | 50 | 11 | 11 | 11 | 5 | 2 | 0 | 1 | 18 | 225 | | 75+ | 41 | 20 | 7 | 18 | 4 | 1 | 0 | 2 | 18 | 84 | | Internet usage | More than once a week | 55 | 10 | 9 | 4 | 3 | 1 | 0 | 0 | 24 | 3,368 | | Once a week or less often | 46 | 11 | 15 | 8 | 3 | 3 | 0 | 1 | 21 | 702 |

1. Base is the quarter-sample of the 2010/11 BCS who were asked questions about internet use who said they had used the internet in the last year but not for online government services.
2. See Section 7.3 of the User Guide for definitions of personal characteristics.

### Table 2.08 Negative experiences in the last year among internet users, by age, sex and internet usage

| Percentages | A computer virus | Unauthorised access to/use of personal data | Upsetting/illegal images | Loss of money | Abusive/threatening behaviour | None of these | Unweighted base¹ | |-------------|-----------------|---------------------------------------------|--------------------------|---------------|-------------------------------|---------------|------------------| | **ALL INTERNET USERS** | 33 | 6 | 4 | 3 | 2 | 61 | 8,383 | | 16-24 | 43 | 6 | 5 | 3 | 6 | 50 | 953 | | 25-34 | 34 | 6 | 3 | 5 | 2 | 60 | 1,498 | | 35-44 | 34 | 7 | 5 | 4 | 2 | 60 | 1,890 | | 45-54 | 35 | 7 | 6 | 3 | 1 | 59 | 1,659 | | 55-64 | 26 | 4 | 3 | 2 | 1 | 69 | 1,393 | | 65-74 | 18 | 2 | 1 | 2 | 0 | 78 | 735 | | 75+ | 17 | 2 | 3 | 2 | 0 | 82 | 255 | | **Men** | 38 | 6 | 4 | 4 | 2 | 57 | 3,891 | | 16-24 | 48 | 7 | 5 | 4 | 5 | 45 | 426 | | 25-34 | 38 | 6 | 4 | 5 | 2 | 57 | 662 | | 35-44 | 39 | 7 | 5 | 5 | 1 | 56 | 867 | | 45-54 | 39 | 7 | 7 | 3 | 1 | 54 | 767 | | 55-64 | 32 | 5 | 2 | 2 | 1 | 63 | 646 | | 65-74 | 20 | 3 | 2 | 3 | 0 | 76 | 384 | | 75+ | 22 | 3 | 3 | 3 | 1 | 77 | 139 | | **Women** | 29 | 5 | 4 | 3 | 2 | 65 | 4,492 | | 16-24 | 38 | 6 | 4 | 2 | 6 | 55 | 527 | | 25-34 | 29 | 7 | 3 | 4 | 2 | 64 | 836 | | 35-44 | 29 | 6 | 5 | 3 | 2 | 65 | 1,023 | | 45-54 | 30 | 6 | 4 | 3 | 0 | 64 | 892 | | 55-64 | 21 | 4 | 3 | 2 | 1 | 75 | 747 | | 65-74 | 16 | 1 | 1 | 1 | 1 | 81 | 351 | | 75+ | 10 | 0 | 2 | 1 | 0 | 89 | 116 | | **Internet usage** | | | | | | | | | More than once a week | 35 | 6 | 4 | 3 | 2 | 59 | 7,542 | | Once a week or less often | 17 | 2 | 2 | 1 | 1 | 79 | 840 |

¹. Base is the quarter-sample of the 2010/11 BCS who were asked questions about internet use who said they had used the internet in the last year.

2. See Section 7.3 of the User Guide for definitions of personal characteristics. 3 Experimental statistics on the experience of crime among children aged 10 to 15

Ivy Lau and Jacqueline Hoare

3.1 SUMMARY

This chapter is based on data collected from 10 to 15 year olds who took part in the 2010/11 British Crime Survey (BCS). Questions were asked of children in England and Wales who had experienced a crime about the circumstances of the incident, any details on the offender(s) and their views of the incident.

The nature of violence

Any differences between the nature of violent incidents experienced by children and adults have been highlighted here, although these naturally reflect the differing lifestyles of children and adults.

- The majority of violent incidents experienced by children took place in or around school (56%) whereas for adults most incidents took place on the street (30%).
- The vast majority of violent incidents experienced by children took place on a weekday (89%) and during daylight (88%) in contrast with adults who tended to experience violent incidents during the evening or at night (67%).
- Violent incidents experienced by children were more likely to involve an offender that was well known to the victim (56%) than incidents experienced by adults (34%).
- Around three-fifths of violent incidents among children involved a single offender (61%), and one-fifth (22%) involved four or more offenders, a similar distribution to adult incidents (66% and 19% respectively).

The nature of theft

- Around half (46%) of incidents of theft experienced by children occurred in or around school.
- Similar to violent incidents, thefts experienced by children were most likely to have occurred during a weekday (85%) and to have taken place during daylight hours (86%).
- Incidents of theft were more likely to be perpetrated by a friend than for violent incidents (22% and 7% respectively).
- Items most likely to be stolen included mobile phones (24% of incidents) and bicycles (21%).

Variation in violence victimisation rates among children

- Boys were around twice as likely as girls to have been a victim of violence (9.5% and 4.1% respectively).
- Children with a long-standing illness or disability were more likely to have experienced a violent incident compared with children without an illness or disability (15.0% and 6.1% respectively).
- Children who had been bullied in the last 12 months had a much higher violence victimisation rate (20.8%) than those who had not been bullied (3.3%), not unexpectedly as children perceived that three in five violent incidents (62%) were part of a series of bullying. 3.2 INTRODUCTION

This chapter is based on data collected from 10 to 15 year olds who took part in the 2010/11 British Crime Survey (BCS). Around 3,850 children took part in the survey after being randomly selected from within households already taking part in the main survey.

All children who were interviewed were asked questions about their experience of crime (details of the questions are published via the Economic and Social Data Service). This chapter reports on the circumstances of violence and theft incidents experienced by 10-to-15-year-old children in the 12 months prior to interview. Victims of such incidents were asked a series of questions relating to their experience including information about the circumstances of the incident, any details on the offender(s) and the child’s view of the nature of the incident.

Estimates of victimisation for 10 to 15 year olds from the 2010/11 BCS have previously been published as experimental statistics (Chaplin et al., 2011). The information included in this publication provides a more detailed picture of children’s experiences of victimisation and thus a greater understanding of the nature of these crimes. The figures presented are restricted to those included in the more focused method of counting crime against children (the ‘Preferred measure’). This takes into account factors identified as important in determining the severity of an incident and thus includes incidents where:

- the offender was not known (e.g. stranger, tradesman, pupil from another school); or
- the offender was known, but aged 16 or over and not a family member (e.g. neighbour, older friend, teacher); or
- the offender was known and either a family member or aged under 16 (e.g. parent, sibling, school-friend) and there was visible injury or theft or damage involving a ‘high value’ item; or
- a weapon was involved.

The analysis presented in Sections 3.3 and 3.4 about the nature of violence and the nature of theft is based on incidents rather than victims (who may have experienced more than one incident). These data are being published for the first time. In contrast, information presented in section 3.5 on the variation in victimisation rates among children is victim-based data (a victim may experience more than one incident of crime, but would only be included once). See Section 4 of the British Crime Survey Dataset User Guide (Children aged 10 to 15) for more information on victim- and incident-based analysis.

Data on the nature of crimes experienced by adults aged 16 or over from the BCS are published annually. Where possible, comparisons are made here to highlight how similar or different victimisation experiences are for adults and children. Due to the small size of the sample, it is not possible to break down incidents of theft experienced by children into smaller offence groups (theft from the person, for example). Hence it is not possible to compare the nature of theft experienced by children with previously published data on the experience of adult respondents due to the different

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1 http://www.esds.ac.uk/findingData/snDescription.asp?sn=6937 2 For more details see Appendix 1 of Chaplin et al. (2011). 3 If there was more than one offender, the incident was included if just one of the offenders matched this criterion. 4 A ‘weapon’ constitutes any item that was considered to be a weapon by the victim; this includes knives, sticks, stones and bottles. 5 See Section 2.5 of the User Guide for more information. 6 http://www.homeoffice.gov.uk/science-research/research-statistics/crime/crime-statistics/bcs-supplementary-tabs/ presentation of data. Nor is it possible to examine the nature of vandalism incidents due to the small size of the sample.(^7)

Any differences in BCS estimates from the 10-to-15-year-old survey that are described in this chapter are statistically significant at the five per cent level (see Section 8 of the User Guide to Home Office Crime Statistics). Considerably fewer individuals are sampled for the 10-to-15-year-old survey than for the adult survey and therefore estimates based on the 10-to-15-year-old survey have a larger margin of error. This means that, compared with the adult survey, differences between estimates must be larger before we can be confident that they are statistically significant.

Victimisation estimates from BCS interviews with 10 to 15 year olds have been designated as experimental statistics, that is, as new Official Statistics undergoing evaluation and published to involve users and stakeholders in their development as a means to build in quality at an early stage. As such, the statistics are subject to further refinement and review. Hence, figures have not yet been considered for accreditation as National Statistics but this chapter has been produced in compliance with the Official Statistics Code of Practice.(^8)

### 3.3 THE NATURE OF VIOLENCE

According to the 2010/11 BCS, there were an estimated 576,000 incidents of violence experienced by children aged 10 to 15 in the last 12 months (Chaplin et al., 2011). Violence as measured by the BCS includes the offence types of wounding, robbery, assault with minor injury and assault with injury (see Section 5.1 of the User Guide for more details).

Figures presented in this section on violent incidents experienced by children have been compared with the nature of violent incidents experienced by adults(^9) to highlight any variations, although naturally these reflect the differing lifestyles of children and adults.

#### The circumstances of violence

Experimental statistics from the 2010/11 BCS showed that the majority of all violent incidents experienced by children aged 10 to 15 took place in or around school (56%), with 36 per cent outside the school building(^10) and 19 per cent inside the school building (Table 3.01).

Sixteen per cent of incidents occurred around the home(^11) and a further 13 per cent at a park, common or open space.

Obviously, this differs from the nature of violent incidents experienced by adults where most incidents took place on the street (30%) or around the home (26%), and only eight per cent took place around work.(^12) This reflects the different lifestyles of children and adults.

Around nine in ten violent incidents experienced by children took place on a weekday (89%). Three-quarters of incidents (76%) took place during the daytime on a weekday with 13 per cent taking place on a weekday evening (Figure 3.1 and Table 3.02). This contrasts with the experiences of adults where around half (55%) of incidents occurred during the week (Figure 3.1).

While the majority (88%) of violent incidents experienced by 10 to 15 year olds took place during daylight, the majority of incidents experienced by adults (67%) took place during the evening or at night.

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(^7) It would require a large expansion of the sample at substantial cost to provide this more detailed breakdown of theft categories or to present the data on the nature of criminal damage.

(^8) http://www.statisticsauthority.gov.uk/assessment/code-of-practice/index.html

(^9) http://www.homeoffice.gov.uk/publications/science-research-statistics/research-statistics/crime-research/nature-violent-crime

(^10) This comprises playground, street or car park.

(^11) This comprises home, garage, shed, car park or nearby street.

(^12) Includes work premises, whether inside/outside or work garage/car parks. Offenders involved in violence

Given the nature of violent offences, victims of violence are more likely to be able to say something about the offender than for other types of crime (see Box 3.1). This was the case for 93 per cent of violent incidents that children experienced, a lower proportion than for adults (99%).

Around three-fifths of violent incidents among children involved a single offender (61%), and one-fifth (22%) involved four or more offenders (Table 3.03). This was a similar distribution to adult incidents (66% and 19% respectively).

The majority of violent incidents were carried out by someone in the victim’s age group: in three-quarters of incidents (76%) the offender was thought to be aged 10 to 15 by the victim and the majority (68%) were perpetrated by pupil(s) at school.

Box 3.1 Victim’s knowledge of offender(s)

BCS 10-to-15-year-old respondents were asked whether they have any information about the offender(s) for any incidents they had experienced in the 12 months prior to interview. Thus, where the offender-victim relationship or any other information about the offender is stated, the proportion is based on those incidents where the respondent has some knowledge of the offender – this is referred to in the text as “able to say something” about the offender(s).

13 In this chapter ‘the offender’ relates to the one offender in an incident where there was one single offender, but in cases where there was more than one offender, ‘the offender’ relates to at least one of the perpetrators. Most violent incidents experienced by children involved male offender(s) (76%), a similar level to that reported by adult victims of violence (79%).

In the majority of violent incidents experienced by children the offender was known to the respondent (Figure 3.2).

- In around half of violent incidents (56%) the offender was known well to the victim.
- In 30 per cent of violent incidents the victim knew the offender by sight or to speak to.
- In 15 per cent of incidents of violence the child victim stated that the offender was a stranger.

This differs from the nature of violent incidents experienced by adults, where the offender was most commonly a stranger (46%) and in around a third of incidents the offender was well known to the victim (34%; Figure 3.2).(^\\text{14})

**Figure 3.2** Proportion of violent incidents experienced by children and adults by relationship to the offender, 2010/11 BCS

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**Injuries and weapons**

Four in five violent incidents experienced by children aged 10 to 15 resulted in some form of injury (81%), the majority being minor bruising or black eyes (59%). One in ten violent incidents resulted in the victim requiring some form of medical attention (12%; Table 3.04).

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(^{14}) For adults, the offender-victim relationship is classified as ‘strangers’ if the victim did not know and had never seen the offender(s) before (as for children) but also if the victim did not have any information about the offender(s). This has little effect on the proportions as in 99 per cent of violent incidents the adult victim was able to say something about the offender. In just over a half (55%) of violent incidents experienced by adults physical injury was sustained; and a third of incidents resulted in minor bruising or black eyes. This may be a reflection of the differences between children and adults, where adults do not tend to engage in low-level assaults on their peers.

Just under a quarter of violent incidents experienced by 10 to 15 year olds involved the use of a weapon(^\\text{15}) (23%), which was a similar proportion to violent incidents experienced by adults (20%). In violent incidents among children which involved a weapon, the most common weapon involved was a stick, club or hitting instrument (41%). One-quarter of such incidents involved the use of stones, bricks or concrete and one in nine (11%) involved a knife, screwdriver or stabbing instrument (Table 3.05). Caution should be used when interpreting these estimates of the type of weapon used in violent incidents experienced by children as they are based on a low number of cases. For more information on the type of injury sustained by children from the BCS 10-to-15s survey; see Chapter 3 of ‘Crime in England and Wales 2010/11’ (Chaplin et al., 2011).

**Perceptions of violence**

Experimental statistics from the 2010/11 BCS showed that 70 per cent of violent incidents experienced by children aged 10 to 15 were not perceived to be a crime by the victim; with 37 per cent perceiving the incident to be ‘wrong, but not a crime’ and 33 per cent perceiving it as ‘just something that happens’ (Table 3.06).

Children perceived that three in five violent incidents (62%) that took place were part of a series of bullying. For more information on the experience of bullying from the BCS children’s survey see Chapter 3 in ‘Supplementary Volume 3 to Crime in England and Wales 2009/10’ (Hoare et al., 2011).

**Reporting of violence**

Overall, the police came to know about 14 per cent of all violent incidents against 10 to 15 year olds. This is lower than the equivalent figure for adults (41%), which is to be expected considering some of the violence that children experience would likely not be reported to the police and may be dealt with by another authority figure, such as a teacher or parent. Indeed, the majority of violent incidents that occurred in or around school were reported by children to a teacher (85%; Table 3.07).

### 3.4 THE NATURE OF THEFT

According to the 2010/11 BCS, there were an estimated 275,000 incidents of theft experienced by children aged 10 to 15 in the last 12 months (Chaplin et al., 2011).

Estimates of thefts experienced by children on the BCS are based on (see Section 5.2 of the User Guide for more details):

- **Personal thefts:** including theft from the person (snatch theft, stealth theft and attempts) and other theft of personal property (for example, theft of items the respondent was not carrying or holding at the time of incident).

- **Household thefts:** including theft from inside and outside a dwelling and theft of bicycles where the property stolen or damaged belonged *solely* to the child respondent.(^\\text{16})

The nature of overall thefts from the 2010/11 BCS 10-to-15s survey is presented here; the separate theft offences are not reported due to low prevalence in some categories. As previously noted (see

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(^{15}) A ‘weapon’ constitutes any item that was considered to be a weapon by the victim (whether adult or child); this includes knives, sticks, stones and bottles.

(^{16}) This broadens the scope of personal victimisation but may also result in an overlap in theft offences reported on the adult survey; the extent to which this happens will be evaluated in the future. Experimental statistics on the experience of crime among children aged 10 to 15

Section 3.2), it is not possible to make comparisons with the nature of theft experienced by adults. Instead, comparisons are made with the nature of violence experienced by children.

The circumstances of thefts

Experimental statistics from the 2010/11 BCS showed that 46 per cent of theft incidents experienced by children occurred in or around school, a lower proportion than for violent incidents (56%). However, thefts were more likely to occur inside a school building than violent incidents (34% compared with 19%). Incidents of theft were also more likely to occur in or around the home (27%) compared with violent incidents (16%; Table 3.01).

Similar to violent incidents, incidents of theft experienced by 10 to 15 year olds were most likely to have occurred during a weekday (85% of theft incidents similar to 89% of violent incidents) and to have taken place during daylight hours (86% and 88% respectively; Table 3.02).

Offenders involved in thefts

As expected, compared with violent incidents, victims of theft were much less likely to be able to say something about the perpetrator of the incident (for example, because some thefts were of unattended items). The following analysis therefore relates only to the 44 per cent of incidents where the child was able to say something about the offender (see Box 3.1 and Table 3.03).

Two-thirds (65%) of theft incidents experienced by children aged 10 to 15 involved a single offender, which was a similar proportion to that for violent incidents (61%). However, incidents of theft were less likely to involve four or more offenders compared with incidents of violence (9% and 22% respectively).

In 80 per cent of incidents of theft where the victim was able to say something about the offender, the offender was perceived to be aged 10 to 15, a similar proportion to that for violent incidents (76%). Again this suggests that the majority of offences are carried out by perpetrators in the victim’s age group.

In 17 per cent of incidents of theft the offender was a stranger, which was similar to violent incidents (16%). However, there was a lower proportion of theft incidents where the offender was known well (44%) compared with violent incidents (56%).

The victim’s relationship to the offender in incidents of theft generally differed to those in violent incidents. For example, of the incidents where the victim was able to say something about the offender:

- Incidents of theft were less likely to be perpetrated by a pupil from the victim’s own school compared with incidents of violence (54% and 68% respectively).
- Incidents of theft were more likely to be perpetrated by a friend than for violent incidents (22% and 7% respectively).

Items stolen

Four in five (79%) incidents of theft (including attempted thefts) experienced by children resulted in an item being stolen. Items most commonly stolen were (Table 3.08):

- a mobile phone (24% of incidents);
- a bicycle or bicycle parts (21%); • cash (16%); and • clothing (12%).

Perceptions of thefts

Incidents of theft experienced by children aged 10 to 15 were perceived in a different way to violent incidents, for example (Table 3.06):

• Incidents of thefts were more likely to be perceived as a crime compared with violent incidents (55% and 30% respectively). • Theft incidents were much less likely to be perceived as part of a series of bullying compared with violent incidents (13% compared with 62%).

Reporting of thefts

Despite incidents of theft being more likely to be perceived by children as a crime compared with violent incidents, the reporting rates were similar for the two types of offences (Table 3.07):

• Police came to know about 13 per cent of theft incidents experienced by 10 to 15 year olds, similar to the 14 per cent of violent incidents reported to the police. • Eighty-four per cent of theft incidents that occurred in or around school were reported to a teacher as were 85 per cent of violent incidents.

3.5 VARIATION IN VICTIMISATION RATES AMONG CHILDREN

Headline victimisation rates(^\\text{17}) for violence, theft and vandalism for 10 to 15 year olds from the 2010/11 BCS have previously been published as experimental statistics (Chaplin et al., 2011). Evidence from the main BCS has repeatedly shown that victimisation rates among adults vary depending on the characteristics of victims (see, for example, Flatley et al., 2010); hence similar analysis has now been carried out on the data collected from children.

This section focuses on the variation in victimisation rates according to personal, household and area characteristics(^\\text{18}) (see Tables 3.09 and 3.10). However, some of these demographic characteristics may be inter-related so caution is needed in the interpretation of the effect of these different characteristics when viewed in isolation.

In general, caution should also be used when interpreting estimates that are based on a low number of cases. This is notably true for certain characteristics associated with children in this sample, such as having been bullied or living in a flat or in an area of high physical disorder. It should also be noted that tests of statistical significance are related to sample size; it may be that some apparently large differences shown in the tables are not statistically significant and could be due to sampling variation. Only statistically significant differences are highlighted in the text.

(^{17}) See Section 2.5 of the User Guide for more information about victimisation (prevalence) rates on the BCS. (^{18}) See Section 7 of the User Guide for more details of these characteristics. Overall, there was little variation in theft or damage victimisation rates among children according to associated personal, household or area characteristics (although levels of bike theft were higher for boys (1.8%) than for girls (0.6%)). Hence the following commentary considers only variations in violence and overall crime victimisation rates among children.(^{19})

**Violence victimisation among children**

According to the 2010/11 BCS, 6.9 per cent of children aged 10 to 15 had experienced a violent crime in the last 12 months (Chaplin *et al.*, 2011 and Tables 3.9 and 3.10). Boys were around twice as likely as girls to have been a victim of violence (9.5% and 4.1% respectively). This was also true looking at grouped ages (Table 3.09):

- Boys aged 10 to 12 (9.6%) and also boys aged 13 to 15 (9.4%) were each more likely to have been victims of violence than both girls aged 10 to 12 (4.8%) and girls aged 13 to 15 (3.5%).

Around 3.1 per cent of adults had experienced a violent crime in the last year (Chaplin *et al.*, 2011). Similar to the gender difference noted among children, men were twice as likely to be a victim of violent crime as women (4.1% and 2.2% respectively).(^{20})

The pattern by age was less clear, however, as ten year olds had the highest victimisation rate (11.6%) compared with all other ages (for example, 5.7% of 11 year olds) but there were no statistically significant differences between any of the other ages. Considering other personal characteristics of children, experimental statistics from the 2010/11 BCS showed that:

- Children with a long-standing illness or disability were more than twice as likely to have experienced a violent incident compared with children without an illness or disability (15.0% and 6.1% respectively).

- Children who had been bullied in the last 12 months had a much higher violence victimisation rate (20.8%) than those who had not been bullied (3.3%). This is not unexpected as violence can often form part of the bullying experience. As discussed in Section 3.3, 62 per cent of violent incidents were perceived to be part of a series of bullying.

There was also variation in violence victimisation among children according to some household characteristics (Table 3.10):

- Children who lived in a household with one adult were more likely to have experienced a violent incident in the last year (9.4%) compared with children who lived in a household with more than one adult (6.2%).

- Children who lived in social-rented property had the highest violence victimisation rate (11.6%) compared with 6.6 per cent of children in private-rented accommodation and 5.2 per cent of those in owner-occupied accommodation.

- Children who lived in households with an income of less than £20,000 were more likely to have been a victim of violence (less than £10,000: 12.5%, from £10,000 to less than £20,000: 10.6%) compared with children who lived in households with all higher incomes (for example, £50,000 or more: 5.4%; Figure 3.3).

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(^{19}) Figures presented here are based on the more focused method of counting crime against children (the Preferred measure) which takes into account factors identified as important in determining the severity of an incident but will still include incidents of a serious nature even if they took place at school.

(^{20}) See [http://www.homeoffice.gov.uk/publications/science-research-statistics/research-statistics/crime-research/hosb1011/](http://www.homeoffice.gov.uk/publications/science-research-statistics/research-statistics/crime-research/hosb1011/) for estimates on the proportion of adults who were victims of violence by offence type and personal characteristics in Table 1 of the ‘Demographic tables – Crime in England and Wales 2010/11’. As with adults, violence victimisation rates were higher in more deprived areas. Children living in an area of high physical disorder were around twice as likely to have been a victim of violence as those living in an area that did not have a high level of disorder (12.5% and 6.5% respectively). Similarly, children living in the most deprived output areas according to the crime deprivation index (9.7%) were around twice as likely to have experienced violence in the last year as those living in the least deprived output areas (5.0%).

The level of violence victimisation among 10 to 15 year olds was similar in urban and rural areas (6.9% and 6.7% respectively). This distribution is different to that of adults; adults living in an urban area were more likely to be a victim of a violent offence than those living in a rural area (3.4% compared with 2.0%).

**Overall victimisation among children**

For children, most of the variation seen in being a victim of any crime is due to the variation in violence victimisation, as the smaller degree of variation in theft and damage victimisation rates only has a minor effect.

Experimental statistics from the 2010/11 BCS showed that 11.7 per cent of children aged 10 to 15 had experienced a crime in the last 12 months (Chaplin et al., 2011 and Tables 3.09 and 3.10). This figure encompasses the 11.4 per cent of children who experienced a crime against the person (that is, an offence of violence or theft) and 0.4 per cent who had experienced a crime against personal property (that is, criminal damage, Tables 3.09 and 3.10).

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21 See [http://www.homeoffice.gov.uk/publications/science-research-statistics/research-statistics/crime-research/hosb1011/](http://www.homeoffice.gov.uk/publications/science-research-statistics/research-statistics/crime-research/hosb1011/) for estimates on the proportion of adults who were victims of violence by offence type and personal characteristics in Table 2 of the ‘Demographic tables – Crime in England and Wales 2010/11’. Boys were more likely than girls to have been a victim of any BCS crime (14.6% and 8.6% respectively). There was no variation by age so this held true when looking at grouped ages (Table 3.09):

- Boys aged 10 to 12 (14.5%) and also boys aged 13 to 15 (14.7%) were each more likely to have been victims of crime than girls aged 10 to 12 and girls aged 13 to 15 (both 8.6%).

As shown for violence victimisation, rates of overall victimisation were considerably higher among children with a long-standing illness or disability and those who had been bullied in the last year:

- Children with a long-standing illness or disability were more likely to have been a victim of crime compared with children without an illness or disability (18.8% and 11.0% respectively).

- Children who had been bullied in the last 12 months had a much higher victimisation rate (28.7%) than those who had not been bullied (6.7%).

There were similar patterns for crime victimisation overall as shown for violence victimisation when looking at household characteristics (Table 3.10):

- Children who lived in a household with one adult were more likely to have experienced a crime in the last year (16.0%) compared with children who lived in a household with more than one adult (10.5%).

- Children who lived in social-rented property had the highest victimisation rate (17.4%, compared with 12.0% of children in private-rented accommodation and 9.4% in owner-occupied accommodation).

- Children who lived in households with lower incomes were the most likely to have been a victim of crime (for example, less than £10,000: 18.1%, compared with £50,000 or more: 9.3%).

Again, as for violence, there was a similarity in children’s victimisation rates in urban and rural areas (11.6% and 11.8% respectively). There was also a clear pattern in levels of victimisation according to the crime deprivation index:

- Children living in the most deprived areas (according to the crime deprivation index) were most likely to have been a victim of crime (15.1%), higher than the 12.0 per cent of children in the 60 per cent of areas between the most and least deprived areas. These figures were both higher than the 8.6 per cent of children living in the least deprived areas (according to the crime deprivation index).

______________________________________________________________________

22 This has already been shown for violence, but holds true for theft as well: 11.3 per cent of children who had been bullied in the last month had been victims of theft, higher than the 3.7 per cent of children who had not been bullied.

### Table 3.01 Experimental statistics: Where incidents experienced by children aged 10 to 15 took place

| Percentages | England and Wales, children aged 10–15, 2010/11 BCS | |-------------|-----------------------------------------------------| | | All violence¹ | All thefts¹ | | In or around school | 56 | 46 | | Inside school building | 19 | 34 | | Outside school building (playground/street/car park) | 36 | 12 | | In or around home/housing estate | 16 | 27 | | Park/common/open space | 13 | 7 | | Other public location (incl transport) | 9 | 9 | | Elsewhere | 6 | 10 |

*Unweighted base* 426 312

1. ‘All violence’ includes the offence types of wounding, robbery, assault with minor injury and assault with injury. ‘All thefts’ includes theft from the person and other theft of personal property but also theft from inside and outside a dwelling and theft of bicycles where the property stolen or damaged belonged solely to the child respondent. See Section 5 of the [User Guide](#) for more information on crime types.

### Table 3.02 Experimental statistics: Timing of when incidents experienced by children aged 10 to 15 took place

| Percentages | England and Wales, children aged 10–15, 2010/11 BCS | |-------------|-----------------------------------------------------| | | All violence¹ | All thefts¹ | | Weekday | 89 | 85 | | Weekday daytime | 76 | 75 | | Weekday evening | 13 | 10 | | Weekend² | 11 | 15 |

*Unweighted base* 419 296

Daylight | 88 | 86 | Dark | 6 | 12 | Dawn/dusk | 6 | 2 |

*Unweighted base* 425 297

Term time | 88 | 82 | School holidays | 12 | 18 |

*Unweighted base* 404 298

1. ‘All violence’ includes the offence types of wounding, robbery, assault with minor injury and assault with injury. ‘All thefts’ includes theft from the person and other theft of personal property but also theft from inside and outside a dwelling and theft of bicycles where the property stolen or damaged belonged solely to the child respondent. See Section 5 of the [User Guide](#) for more information on crime types.

2. Weekend includes Friday night. Table 3.03 Experimental statistics: Offender characteristics in incidents experienced by children aged 10 to 15

| Percentages | England and Wales, children aged 10–15, 2010/11 BCS | All violence<sup>1</sup> | All thefts<sup>1</sup> | |-------------|-----------------------------------------------------|--------------------------|------------------------| | Able to say something about offender(s) | 93 | 44 | | Unweighted base | 424 | 309 |

| Number of offender(s) | | | |-----------------------|-----------------|-----------------| | One | 61 | 65 | | Two | 11 | 22 | | Three | 6 | 5 | | Four or more | 22 | 9 |

| Sex of offender(s) | | | |--------------------|-----------------|-----------------| | Male(s) | 76 | 76 | | Female(s) | 16 | 19 | | Both | 8 | 5 |

| Age of offender(s)<sup>2</sup> | | | |-------------------------------|-----------------|-----------------| | Aged under 10 | 10 | 5 | | Aged 10 to 15 | 76 | 80 | | Aged 16 to 19 | 12 | 15 | | Aged 20 or older | 4 | 4 |

| Relationship to victim<sup>3</sup> | | | |-----------------------------------|-----------------|-----------------| | Stranger | 15 | 17 | | Known by sight or to speak to | 30 | 39 | | Known well | 56 | 44 |

Unweighted base (victim was able to say something about the offender) | 395 | 119 |

| Unweighted base (victim was able to say something about an offender who was 'known') | 321 | 98 |

1. 'All violence' includes the offence types of wounding, robbery, assault with minor injury and assault with injury. 'All thefts' includes theft from the person and other theft of personal property but also theft from inside and outside a dwelling and theft of bicycles where the property stolen or damaged belonged solely to the child respondent. See Section 5 of the User Guide for more information on crime types.

2. Figures add to more than 100 as more than one offender could be involved.

3. Where there was more than one offender a priority order was applied to the data so that 'Known well' would take precedence over 'Known by sight or to speak to' which would in turn take precedence over 'Stranger'. For example if there were two offenders, one 'Known well' and the other a 'Stranger' this would be categorised as 'Known well'.

### Table 3.04 Experimental statistics: What injuries were sustained in violent incidents experienced by children aged 10 to 15

| Percentages | England and Wales, children aged 10–15, 2010/11 BCS | All violence¹ | |-------------|---------------------------------------------------|---------------| | Sustained an injury | 81 | | | Received some form of medical attention | 12 | |

*Unweighted base* 414

#### Type of injury

| Minor bruise/black eye | 59 | | Scratches | 31 | | Marks on skin | 19 | | Severe bruising | 14 | | Cuts | 10 | | Serious injury² | 7 | | Hurt but no marks on skin | 5 | | Some other injury | 2 |

*Unweighted base* 294

1. ‘All violence’ includes the offence types of wounding, robbery, assault with minor injury and assault with injury. See Section 5 of the User Guide for more information on crime types.

2. Serious injury includes: facial/head injuries, broken nose, concussion, broken bones.

### Table 3.05 Experimental statistics: What weapons were used in violent incidents experienced by children aged 10 to 15

| Percentages | England and Wales, children aged 10–15, 2010/11 BCS | All violence¹ | |-------------|---------------------------------------------------|---------------| | Weapon used | 23 | |

*Unweighted base* 403

| Stick/club/hitting implement | 41 | | Stones/brick/concrete | 25 | | Knife/screwdriver/stabbing implement | 11 | | Something else | 33 |

*Unweighted base* 106

1. ‘All violence’ includes the offence types of wounding, robbery, assault with minor injury and assault with injury. See Section 5 of the User Guide for more information on crime types.

### Table 3.06 Experimental statistics: Perceptions of incidents experienced by children aged 10 to 15

| Percentages | England and Wales, children aged 10–15, 2010/11 BCS | All violence¹ | All thefts¹ | |----------------------------------------------------------------------------|-----------------------------------------------------|---------------|-------------| | Incident perceived as a crime | | 30 | 55 | | Incident not perceived as a crime | | 70 | 45 | | Incident perceived to be wrong, but not a crime | | 37 | 24 | | Incident perceived to be just something that happens | | 33 | 21 | | **Unweighted base** | | 412 | 307 | | Incident perceived as part of a series of bullying | | 62 | 13 | | **Unweighted base** | | 403 | 306 |

¹. ‘All violence’ includes the offence types of wounding, robbery, assault with minor injury and assault with injury. ‘All thefts’ includes theft from the person and other theft of personal property but also theft from inside and outside a dwelling and theft of bicycles where the property stolen or damaged belonged solely to the child respondent. See Section 5 of the User Guide for more information on crime types.

### Table 3.07 Experimental statistics: Who incidents experienced by children aged 10 to 15 were reported to

| Percentages | England and Wales, children aged 10–15, 2010/11 BCS | All violence¹ | All thefts¹ | |----------------------------------------------------------------------------|-----------------------------------------------------|---------------|-------------| | Whether police came to know about the incident | | 14 | 13 | | **Unweighted base** | | 423 | 308 | | Reported to at school | | | | | Teacher | | 85 | 84 | | Friend | | 17 | 27 | | Someone else at school (incl prefect) | | 15 | 18 | | **Unweighted base (only includes incidents that occurred at school)** | | 138 | 106 |

¹. ‘All violence’ includes the offence types of wounding, robbery, assault with minor injury and assault with injury. ‘All thefts’ includes theft from the person and other theft of personal property but also theft from inside and outside a dwelling and theft of bicycles where the property stolen or damaged belonged solely to the child respondent. See Section 5 of the User Guide for more information on crime types. Table 3.08 Experimental statistics: What items were stolen in thefts experienced by children aged 10 to 15

| Percentages | England and Wales, children aged 10–15, 2010/11 BCS | All thefts¹ | |-------------|---------------------------------------------------|-------------| | Any item was stolen² | 79 | | | Unweighted base | 312 | |

| Type of item stolen | | |---------------------|---| | Mobile phone | 24 | | Bicycle or bicycle parts | 21 | | Cash/foreign currency | 16 | | Clothing | 12 | | Electrical items | 7 | | Bag/handbag/shopping bag | 7 | | Sports equipment | 5 | | Toys | 4 | | Stationery/books | 4 | | Jewellery/watches | 3 | | Cards/purse | 2 | | Other items | 12 |

Unweighted base 247

1. ‘All thefts’ includes theft from the person and other theft of personal property but also theft from inside and outside a dwelling and theft of bicycles where the property stolen or damaged belonged solely to the child respondent. See Section 5 of the User Guide for more information on crime types.
2. Proportion is based on all thefts, including attempted thefts where no items were stolen.

### Table 3.09 Experimental statistics: Proportion of children aged 10 to 15 who experienced victimisation in the last year, by personal characteristics

| Percentages | All violence | All thefts | Crime against the person | Crime against personal property | All crime experienced by children aged 10–15 | |-------------|--------------|------------|--------------------------|---------------------------------|---------------------------------------------| | | Violence with injury | Violence without injury | Theft from the person | Other theft of personal property | Theft from the dwelling/ outside the dwelling | Bike theft | Unweighted base | | ALL CHILDREN AGED 10–15 | 6.9 | 5.1 | 2.1 | 5.4 | 0.7 | 3.1 | 0.5 | 1.2 | 11.4 | 0.4 | 11.7 | 3,849 | | Age | | | | | | | | | | | | | | 10–12 | 7.3 | 5.6 | 2.0 | 5.1 | 0.5 | 2.9 | 0.6 | 1.2 | 11.4 | 0.6 | 11.6 | 1,823 | | 10 | 11.6 | 9.4 | 2.5 | 4.0 | 0.0 | 2.5 | 0.6 | 0.8 | 14.6 | 1.2 | 15.0 | 532 | | 11 | 5.7 | 4.3 | 1.9 | 5.6 | 0.9 | 3.2 | 0.5 | 1.3 | 10.4 | 0.6 | 10.7 | 640 | | 12 | 5.0 | 3.6 | 1.8 | 5.5 | 0.5 | 3.0 | 0.5 | 1.5 | 9.5 | 0.1 | 9.6 | 651 | | 13–15 | 6.5 | 4.6 | 2.2 | 5.7 | 0.8 | 3.3 | 0.5 | 1.2 | 11.5 | 0.2 | 11.7 | 2,026 | | 13 | 7.1 | 4.9 | 2.6 | 4.3 | 0.5 | 3.0 | 0.5 | 0.4 | 11.1 | 0.6 | 11.4 | 685 | | 14 | 6.1 | 4.1 | 2.2 | 6.3 | 1.1 | 3.3 | 0.2 | 1.7 | 11.2 | 0.0 | 11.2 | 646 | | 15 | 6.3 | 4.7 | 1.7 | 6.6 | 1.0 | 3.6 | 0.7 | 1.6 | 12.3 | 0.1 | 12.3 | 695 | | Boys | | | | | | | | | | | | | | 10–12 | 9.5 | 6.9 | 3.1 | 6.0 | 0.8 | 2.9 | 0.5 | 1.8 | 14.2 | 0.7 | 14.6 | 1,974 | | 10 | 9.6 | 7.2 | 3.0 | 6.1 | 0.8 | 3.0 | 0.6 | 1.9 | 14.1 | 0.9 | 14.5 | 933 | | 13–15 | 9.4 | 6.7 | 3.1 | 5.8 | 0.7 | 2.9 | 0.4 | 1.8 | 14.4 | 0.5 | 14.7 | 1,041 | | Girls | | | | | | | | | | | | | | 10–12 | 4.1 | 3.1 | 1.1 | 4.8 | 0.6 | 3.3 | 0.5 | 0.6 | 8.5 | 0.1 | 8.6 | 1,875 | | 10 | 4.8 | 3.9 | 1.0 | 3.9 | 0.2 | 2.8 | 0.5 | 0.6 | 8.4 | 0.3 | 8.6 | 890 | | 13–15 | 3.5 | 2.4 | 1.2 | 5.6 | 0.9 | 3.7 | 0.5 | 0.6 | 8.6 | 0.0 | 8.6 | 985 | | Ethnic group | | | | | | | | | | | | | | White | 7.1 | 5.0 | 2.4 | 5.4 | 0.6 | 3.1 | 0.6 | 1.2 | 11.6 | 0.5 | 11.8 | 3,343 | | Ethnic group other than White | 6.0 | 5.4 | 0.6 | 5.5 | 1.1 | 3.2 | 0.0 | 1.2 | 10.9 | 0.2 | 10.9 | 498 | | School year | | | | | | | | | | | | | | Year 5 | 11.5 | 9.1 | 2.6 | 4.1 | 0.0 | 2.8 | 0.3 | 1.0 | 14.8 | 1.1 | 15.6 | 272 | | Year 6 | 8.6 | 7.2 | 2.1 | 5.5 | 0.5 | 2.8 | 1.1 | 1.5 | 13.0 | 1.0 | 13.2 | 548 | | Year 7 | 4.5 | 3.6 | 1.0 | 5.3 | 0.6 | 3.2 | 0.3 | 1.2 | 8.5 | 0.4 | 8.8 | 642 | | Year 8 | 7.2 | 5.0 | 2.5 | 4.3 | 0.5 | 2.4 | 0.4 | 0.9 | 10.8 | 0.0 | 10.8 | 659 | | Year 9 | 6.3 | 3.9 | 2.7 | 5.3 | 1.1 | 2.9 | 0.3 | 1.0 | 11.2 | 0.6 | 11.5 | 673 | | Year 10 | 5.6 | 3.9 | 2.0 | 6.1 | 0.9 | 3.6 | 0.2 | 1.5 | 10.8 | 0.0 | 10.8 | 687 | | Year 11 | 6.8 | 5.6 | 1.2 | 7.8 | 1.0 | 4.4 | 1.3 | 1.4 | 13.8 | 0.1 | 13.9 | 347 | | Long-standing illness or disability | | | | | | | | | | | | | | Long-standing illness or disability | 15.0 | 11.6 | 3.8 | 4.9 | 0.8 | 2.6 | 0.6 | 1.0 | 18.5 | 0.4 | 18.8 | 335 | | No long-standing illness or disability | 6.1 | 4.4 | 2.0 | 5.4 | 0.6 | 3.2 | 0.5 | 1.2 | 10.8 | 0.4 | 11.0 | 3,506 | | Experience of bullying | | | | | | | | | | | | | | Bullied in last 12 months | 20.8 | 16.7 | 6.3 | 11.3 | 2.3 | 7.7 | 0.2 | 1.3 | 26.7 | 0.2 | 26.7 | 229 | | Not bullied in last 12 months | 3.3 | 2.4 | 0.9 | 3.7 | 0.2 | 1.9 | 0.3 | 1.3 | 6.6 | 0.1 | 6.7 | 971 |

1. 'All violence' includes the offence types of wounding, robbery, assault with minor injury and assault with injury. 'All thefts' includes theft from the person and other theft of personal property but also theft from inside and outside a dwelling and theft of bicycles where the property stolen or damaged belonged solely to the child respondent. 'Crime against the person' comprises all violence and thefts. See Section 5 of the User Guide for more information on crime types.
2. As the BCS includes 10 to 15 year olds, Year 5 represents only pupils aged 10 and Year 11 only pupils aged 15.
3. Question asked in the self-completion module of a third of the sample.
4. See Section 7.3 of the User Guide for definitions of personal characteristics. Table 3.10 Experimental statistics: Proportion of children aged 10 to 15 who experienced victimisation in the last year, by household and area characteristics

| Percentages | All violence | All thefts | Crime against | Crime against | All crime | Unweighted | |-------------|-------------|------------|---------------|---------------|-----------|------------| | | Violence with injury | Violence without injury | Theft from the person | Other theft of personal property | Theft from the dwelling/ outside the dwelling | Bike theft | the person | personal property | experienced by children aged 10–15 | base | | ALL CHILDREN AGED 10–15 | 6.9 | 5.1 | 2.1 | 5.4 | 0.7 | 3.1 | 0.5 | 1.2 | 11.4 | 0.4 | 11.7 | 3,849 | | Structure of household | | | | | | | | | | | | | | Single adult & child(ren) | 9.4 | 7.0 | 2.8 | 7.1 | 0.9 | 4.2 | 0.6 | 1.7 | 15.6 | 0.7 | 16.0 | 726 | | Adults & child(ren) | 6.2 | 4.6 | 1.9 | 5.0 | 0.6 | 2.8 | 0.5 | 1.1 | 10.4 | 0.3 | 10.5 | 3,123 | | Total household income | | | | | | | | | | | | | | Less than £10,000 | 12.5 | 10.6 | 2.5 | 6.9 | 1.9 | 1.8 | 0.9 | 2.5 | 17.8 | 0.3 | 18.1 | 329 | | £10,000 less than £20,000 | 10.6 | 8.1 | 3.2 | 6.3 | 0.6 | 4.5 | 0.2 | 1.1 | 15.8 | 0.9 | 16.1 | 695 | | £20,000 less than £30,000 | 6.5 | 5.0 | 1.8 | 6.3 | 0.7 | 3.4 | 0.5 | 1.7 | 11.7 | 0.6 | 11.9 | 547 | | £30,000 less than £40,000 | 4.4 | 2.6 | 2.0 | 5.3 | 0.7 | 2.8 | 0.5 | 1.8 | 9.1 | 0.0 | 9.1 | 474 | | £40,000 less than £50,000 | 4.9 | 3.5 | 1.8 | 4.4 | 0.8 | 3.2 | 0.0 | 0.3 | 8.9 | 0.8 | 9.7 | 377 | | £50,000 or more | 5.4 | 3.3 | 2.3 | 4.5 | 0.3 | 3.1 | 0.6 | 0.8 | 9.3 | 0.0 | 9.3 | 778 | | No income stated or not enough information provided | 4.5 | 3.5 | 1.0 | 4.5 | 0.5 | 2.3 | 0.9 | 0.9 | 8.5 | 0.3 | 8.6 | 648 | | Tenure | | | | | | | | | | | | | | Owners | 5.2 | 3.6 | 1.7 | 4.6 | 0.5 | 2.8 | 0.5 | 0.9 | 9.2 | 0.3 | 9.4 | 2,464 | | Social renters | 11.6 | 8.7 | 3.4 | 7.1 | 0.9 | 3.6 | 0.7 | 2.1 | 17.2 | 0.6 | 17.4 | 790 | | Private renters | 6.6 | 5.5 | 1.6 | 6.1 | 1.1 | 3.4 | 0.4 | 1.1 | 11.7 | 0.7 | 12.0 | 588 | | Accommodation type | | | | | | | | | | | | | | Houses | 6.8 | 5.0 | 2.0 | 5.4 | 0.7 | 3.0 | 0.5 | 1.2 | 11.4 | 0.4 | 11.6 | 3,603 | | Detached | 5.4 | 3.4 | 2.0 | 3.7 | 0.3 | 2.7 | 0.2 | 0.6 | 8.6 | 0.1 | 8.6 | 1,079 | | Semi-detached | 7.4 | 5.4 | 2.4 | 5.7 | 0.8 | 3.1 | 0.5 | 1.3 | 12.5 | 0.5 | 12.9 | 1,406 | | Terraced | 7.2 | 5.9 | 1.6 | 6.3 | 0.9 | 3.1 | 0.8 | 1.6 | 12.3 | 0.4 | 12.5 | 1,118 | | Flats/maisonettes | 9.3 | 6.6 | 3.9 | 5.8 | 0.5 | 4.5 | 0.5 | 0.8 | 13.5 | 1.0 | 13.5 | 196 | | Output area classification | | | | | | | | | | | | | | Blue collar communities | 10.7 | 8.0 | 3.2 | 4.8 | 0.6 | 2.4 | 0.8 | 1.2 | 14.3 | 0.5 | 14.6 | 771 | | City living | 5.0 | 4.5 | 0.6 | 7.1 | 1.2 | 3.9 | 0.9 | 1.1 | 10.1 | 2.0 | 10.1 | 92 | | Countryside | 5.1 | 3.9 | 1.2 | 5.4 | 0.7 | 4.2 | 0.2 | 0.3 | 9.7 | 0.8 | 9.4 | 569 | | Prospering suburbs | 4.7 | 3.0 | 2.0 | 4.9 | 0.4 | 3.1 | 0.3 | 1.4 | 9.4 | 0.3 | 9.6 | 364 | | Constrained by circumstances | 9.9 | 6.2 | 4.5 | 8.1 | 0.7 | 4.5 | 1.3 | 1.8 | 16.5 | 0.6 | 16.5 | 301 | | Typical traits | 7.4 | 5.8 | 1.7 | 5.1 | 0.6 | 2.6 | 0.7 | 1.4 | 11.4 | 0.3 | 11.4 | 767 | | Multicultural | 4.3 | 3.6 | 1.0 | 5.5 | 1.3 | 2.9 | 0.0 | 1.3 | 9.6 | 0.1 | 9.6 | 385 | | Area type | | | | | | | | | | | | | | Urban | 6.9 | 5.1 | 2.1 | 5.3 | 0.6 | 2.9 | 0.5 | 1.3 | 11.4 | 0.4 | 11.6 | 2,888 | | Rural | 6.7 | 4.9 | 2.2 | 5.9 | 0.9 | 3.7 | 0.5 | 0.8 | 11.6 | 0.5 | 11.8 | 961 | | Level of physical disorder | | | | | | | | | | | | | | High | 12.5 | 7.5 | 6.6 | 6.4 | 1.5 | 3.9 | 0.0 | 1.4 | 17.3 | 0.0 | 17.3 | 215 | | Not high | 6.5 | 4.9 | 1.8 | 5.3 | 0.6 | 3.1 | 0.6 | 1.2 | 11.1 | 0.5 | 11.3 | 3,581 | | English Indices of Deprivation (Employment) | | | | | | | | | | | | | | 20% most deprived output areas | 8.6 | 6.1 | 3.0 | 5.9 | 1.0 | 2.8 | 0.3 | 1.9 | 13.7 | 0.2 | 13.9 | 685 | | Other output areas | 6.7 | 5.2 | 1.8 | 5.2 | 0.6 | 3.2 | 0.6 | 1.0 | 11.1 | 0.6 | 11.4 | 2,134 | | 20% least deprived output areas | 6.1 | 4.0 | 2.3 | 5.5 | 0.9 | 3.4 | 0.3 | 1.1 | 11.0 | 0.0 | 11.0 | 748 | | English Indices of Deprivation (Crime) | | | | | | | | | | | | | | 20% most deprived output areas | 9.7 | 6.8 | 3.3 | 6.0 | 0.4 | 3.2 | 0.3 | 2.1 | 14.8 | 0.6 | 15.1 | 612 | | Other output areas | 6.8 | 5.3 | 1.8 | 5.8 | 0.9 | 3.0 | 0.6 | 1.3 | 11.7 | 0.4 | 12.0 | 2,077 | | 20% least deprived output areas | 5.0 | 3.2 | 2.1 | 4.0 | 0.4 | 3.4 | 0.1 | 0.1 | 8.6 | 0.2 | 8.6 | 878 |

1. ‘All violence’ includes the offence types of wounding, robbery, assault with minor injury and assault with injury. ‘All thefts’ includes theft from the person and other theft of personal property but also theft from inside and outside a dwelling and theft of bicycles where the property stolen or damaged belonged solely to the child respondent. ‘Crime against the person’ comprises all violence and thefts. See Section 5 of the User Guide for more information on crime types.

2. See Sections 7.1 and 7.2 of the User Guide for definitions of area and household characteristics. Bibliography

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Chaplin, R., Flatley, J. and Smith, K. (Eds.) (2011) Crime in England and Wales 2010/11: Findings from the British Crime Survey and police recorded crime. Home Office Statistical Bulletin 10/11. London: Home Office. http://www.homeoffice.gov.uk/publications/science-research-statistics/research-statistics/crime-research/hosb1011/

Flatley, J., Kershaw, C., Smith, K., Chaplin, R. and Moon, D. (Eds.) (2010) Crime in England and Wales 2009/10: Findings from the British Crime Survey and police recorded crime. Home Office Statistical Bulletin 12/10. London: Home Office. http://www.homeoffice.gov.uk/publications/science-research-statistics/research-statistics/crime-research/hosb1210/

Garcia, L., McDevitt, J., Gu, J. and Balboni, J. (1999) Psychological and Behavioural Effects of Bias and Non-Bias Motivated Assault, Final Report. National Criminal Justice Reference Service, December 1999, pp. 53–55, 87 and 94–95.

Hoare, J., Parfrement-Hopkins, J., Britton, A., Hall, P., Scribbins, M. (Ed.) and Flatley, J. (Ed.) (2011) Children’s experience and attitudes towards the police, personal safety and public spaces: Findings from the 2009/10 British Crime Survey interviews with children aged 10 to 15. Home Office Statistical Bulletin 08/11. London: Home Office. http://www.homeoffice.gov.uk/publications/science-research-statistics/research-statistics/crime-research/hosb0811/?view=Standard&pubID=889889

Home Office (2010) User Guide to Home Office Crime Statistics. London: Home Office. http://www.homeoffice.gov.uk/publications/science-research-statistics/research-statistics/crime-research/user-guide-crime-statistics/?view=Standard&pubID=866666

Iganski, P. (2001) Hate Crimes Hurt More. American Behavioral Scientist 45 (4). pp. 626–38.

Iganski, P. (2008) Hate Crime and the City. Bristol: Policy Press.

Jansson, K. (2006) Black and Minority Ethnic groups’ experiences and perceptions of crime, racially motivated crime and the police: findings from the 2004/05 British Crime Survey. Home Office Online Report 25/06. London: Home Office. http://webarchive.nationalarchives.gov.uk/20110218135832/http://rds.homeoffice.gov.uk/rds/pdfs06/rdsoir2506.pdf

Jansson, K., Budd, S., Lovbakke, J., Moley, S. and Thorpe, K. (2007) Attitudes, perceptions and risks of crime: Supplementary Volume 1 to Crime in England and Wales 2006/07. Home Office Statistical Bulletin 19/07. London: Home Office. http://webarchive.nationalarchives.gov.uk/20110218135832/rdsoir2506/rdsoir1907.pdf

Moon, D. (Ed.), Flatley, J. (Ed.), Hoare, J., Green, B. and Murphy, R. (2010) Acquisitive crime and plastic card fraud: Findings from the 2008/09 British Crime Survey. Home Office Statistical Bulletin 08/10. London: Home Office. http://webarchive.nationalarchives.gov.uk/20110218135832/rdsoir2506/rdsoir0810.pdf Salisbury, H., and Upson, A. (2004) *Ethnicity, victimisation and worry about crime: findings from the 2001/02 and 2002/03 British Crime Surveys*. Home Office Research Findings 237. London: Home Office.\
http://webarchive.nationalarchives.gov.uk/20110218135832/http://rds.homeoffice.gov.uk/rds/pdfs04/r237.pdf

Copies of Home Office publications are available from the Home Office Science internet pages: http://homeoffice.gov.uk/science-research/research-statistics/